@misc{GuentherLameckerWeiser, author = {G{\"u}nther, Andreas and Lamecker, Hans and Weiser, Martin}, title = {Direct LDDMM of Discrete Currents with Adaptive Finite Elements}, doi = {10.1007/s11263-012-0599-3}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-13090}, number = {11-22}, abstract = {We consider Large Deformation Diffeomorphic Metric Mapping of general \$m\$-currents. After stating an optimization algorithm in the function space of admissable morph generating velocity fields, two innovative aspects in this framework are presented and numerically investigated: First, we spatially discretize the velocity field with conforming adaptive finite elements and discuss advantages of this new approach. Second, we directly compute the temporal evolution of discrete \$m\$-current attributes.}, language = {en} } @inproceedings{LameckerSeebassHegeetal.2004, author = {Lamecker, Hans and Seebaß, Martin and Hege, Hans-Christian and Deuflhard, Peter}, title = {A 3d statistical shape model of the pelvic bone for segmentation}, series = {Proc. SPIE Medical Imaging 2004}, volume = {5370}, booktitle = {Proc. SPIE Medical Imaging 2004}, editor = {Fitzpatrick, J. and Sonka, Milan}, pages = {1341 -- 1351}, year = {2004}, language = {en} } @inproceedings{LameckerSeebassLangeetal.2004, author = {Lamecker, Hans and Seebass, Martin and Lange, Thomas and Hege, Hans-Christian and Deuflhard, Peter}, title = {Visualization of the variability of 3D statistical shape models by animation}, series = {Proc. Medicine Meets Virtual Reality}, volume = {98}, booktitle = {Proc. Medicine Meets Virtual Reality}, editor = {Westwood, J.}, publisher = {IOS Press}, pages = {190 -- 196}, year = {2004}, language = {en} } @article{TodtLameckerRammetal.2014, author = {Todt, Ingo and Lamecker, Hans and Ramm, Heiko and Frenzel, Henning and Wollenberg, Barbara and Beleites, Thomas and Zahnert, Thomas and Thomas, Jan Peter and Dazert, Stefan and Ernst, Arneborg}, title = {Entwicklung eines CT-Daten-basierten Vibrant-Bonebridge-Viewers}, series = {HNO}, volume = {62}, journal = {HNO}, publisher = {Springer}, doi = {10.1007/s00106-014-2851-3}, pages = {439 -- 442}, year = {2014}, abstract = {Die Positionierung des B-FMT der Vibrant Bonebridge kann aufgrund der anatomischen Verh{\"a}ltnisse des Mastoids und der Gr{\"o}ße des Aktuators ohne eine vorherige Beurteilung der individuellen Computertomographie (CT) des Felsenbeins problematisch sein. Die Entwicklung eines einfach zu bedienenden Viewers, welcher eine Positionierung des B-FMT im Felsenbeinmodell erm{\"o}glicht und hier auf individuelle potenzielle anatomische Konflikte hinweist sowie L{\"o}sungsm{\"o}glichkeiten anbietet, kann ein hilfreiches Werkzeug zur pr{\"a}operativen Positionierung sein. Ziel der Arbeit war die Definition von Anforderungen und die Anfertigung eines Prototyps eines Vibrant-Bonebridge-Viewers. Auf der Basis einer ZIBAmira-Software-Version und der Inklusion eines B-FMT-Modells unter Erstellung eines Felsenbeinmodells, welches die intuitive Beurteilung von Konflikten erm{\"o}glicht, erfolgte die Erstellung des Prototyps eines Vibrant-Bonebridge-Viewers.Ergebnisse. Die Segmentierungszeit der individuellen DICOM-Daten („digital imaging and communications in medicine") betr{\"a}gt etwa 5 min. Eine Positionierung im individuellen 3-D-Felsenbeinmodell erm{\"o}glicht die quantitative und qualitative Beurteilung von Konflikten (Sinus sigmoideus, mittlere Sch{\"a}delgrube) und das Aufsuchen einer bevorzugten Position. Das Anheben des B-FMT mittels virtueller Unterlegscheiben kann simuliert werden. Der erstellte Vibrant-Bonebridge-Viewer erm{\"o}glicht verl{\"a}sslich eine Simulation der B-FMT-Positionierung. Die klinische Anwendbarkeit muss evaluiert werden.}, language = {de} } @article{TodtLameckerRammetal., author = {Todt, Ingo and Lamecker, Hans and Ramm, Heiko and Ernst, Arneborg}, title = {A computed tomographic data-based vibrant bonebridge visualization tool}, series = {Cochlear Implants International}, volume = {15}, journal = {Cochlear Implants International}, number = {S1}, doi = {10.1179/1467010014Z.000000000155}, pages = {72 -- 74}, abstract = {Information about the temporal bone size and variations of anatomical structures are crucial for a safe positioning of the Vibrant Bonebridge B-FMT. A radiological based preoperative planning of the surgical procedure decreases the surgical time and minimizes the risk of complications. We developed a software tool, which allows a catch up of foreign DICOM data based CT temporal bone scans. The individual CT scan is transmitted into a 3D reconstructed pattern of the temporal bone. In this 3D reconstruction the individually favored position of the B- FMT should be found. The software allows a determination of a safe B-FMT position by identifying the individual relation of middle fossa, jugular bulb and external auditory canal. Skull thickness and screw length are contained parameters for the surgical planning. An easy to handle software tool allows a radiologically data based safe and fast surgical positioning of the B-FMT.}, language = {en} } @article{HochfeldLameckerThomaleetal., author = {Hochfeld, Mascha and Lamecker, Hans and Thomale, Ulrich W. and Schulz, Matthias and Zachow, Stefan and Haberl, Hannes}, title = {Frame-based cranial reconstruction}, series = {Journal of Neurosurgery: Pediatrics}, volume = {13}, journal = {Journal of Neurosurgery: Pediatrics}, number = {3}, doi = {10.3171/2013.11.PEDS1369}, pages = {319 -- 323}, abstract = {The authors report on the first experiences with the prototype of a surgical tool for cranial remodeling. The device enables the surgeon to transfer statistical information, represented in a model, into the disfigured bone. The model is derived from a currently evolving databank of normal head shapes. Ultimately, the databank will provide a set of standard models covering the statistical range of normal head shapes, thus providing the required template for any standard remodeling procedure as well as customized models for intended overcorrection. To date, this technique has been used in the surgical treatment of 14 infants (age range 6-12 months) with craniosynostosis. In all 14 cases, the designated esthetic result, embodied by the selected model, has been achieved, without morbidity or mortality. Frame-based reconstruction provides the required tools to precisely realize the surgical reproduction of the model shape. It enables the establishment of a self-referring system, feeding back postoperative growth patterns, recorded by 3D follow-up, into the model design.}, language = {en} } @inproceedings{AmbellanTackWilsonetal., author = {Ambellan, Felix and Tack, Alexander and Wilson, Dave and Anglin, Carolyn and Lamecker, Hans and Zachow, Stefan}, title = {Evaluating two methods for Geometry Reconstruction from Sparse Surgical Navigation Data}, series = {Proceedings of the Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- und Roboterassistierte Chirurgie (CURAC)}, volume = {16}, booktitle = {Proceedings of the Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- und Roboterassistierte Chirurgie (CURAC)}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-65339}, pages = {24 -- 30}, abstract = {In this study we investigate methods for fitting a Statistical Shape Model (SSM) to intraoperatively acquired point cloud data from a surgical navigation system. We validate the fitted models against the pre-operatively acquired Magnetic Resonance Imaging (MRI) data from the same patients. We consider a cohort of 10 patients who underwent navigated total knee arthroplasty. As part of the surgical protocol the patients' distal femurs were partially digitized. All patients had an MRI scan two months pre-operatively. The MRI data were manually segmented and the reconstructed bone surfaces used as ground truth against which the fit was compared. Two methods were used to fit the SSM to the data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). For both approaches, the difference between model fit and ground truth surface averaged less than 1.7 mm and excellent correspondence with the distal femoral morphology can be demonstrated.}, language = {en} } @misc{BindernagelKainmuellerRammetal.2012, author = {Bindernagel, Matthias and Kainm{\"u}ller, Dagmar and Ramm, Heiko and Lamecker, Hans and Zachow, Stefan}, title = {Analysis of inter-individual anatomical shape variations of joint structures}, series = {Proc. Int. Society of Computer Assisted Orthopaedic Surgery (CAOS)}, journal = {Proc. Int. Society of Computer Assisted Orthopaedic Surgery (CAOS)}, number = {210}, year = {2012}, language = {en} } @inproceedings{NguyenLameckerKainmuelleretal.2012, author = {Nguyen, The Duy and Lamecker, Hans and Kainm{\"u}ller, Dagmar and Zachow, Stefan}, title = {Automatic Detection and Classification of Teeth in CT Data}, series = {Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI)}, volume = {7510}, booktitle = {Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI)}, editor = {Ayache, Nicholas and Delingette, Herv{\´e} and Golland, Polina and Mori, Kensaku}, pages = {609 -- 616}, year = {2012}, language = {en} } @article{NguyenKainmuellerLameckeretal.2012, author = {Nguyen, The Duy and Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan}, title = {Automatic bone and tooth detection for CT-based dental implant planning}, series = {Int. J. Computer Assisted Radiology and Surgery}, volume = {7, Supplement 1}, journal = {Int. J. Computer Assisted Radiology and Surgery}, number = {1}, publisher = {Springer}, pages = {293 -- 294}, year = {2012}, language = {en} } @inproceedings{LameckerZoecklerHaberletal.2005, author = {Lamecker, Hans and Z{\"o}ckler, Maja and Haberl, Hannes and Zachow, Stefan and Hege, Hans-Christian}, title = {Statistical shape modeling for craniosynostosis planning}, series = {2nd International Conference Advanced Digital Technology in Head and Neck Reconstruction 2005, Abstract Volume}, booktitle = {2nd International Conference Advanced Digital Technology in Head and Neck Reconstruction 2005, Abstract Volume}, address = {Banff, Alberta}, pages = {64}, year = {2005}, language = {en} } @inproceedings{LangeWenckebachLameckeretal.2005, author = {Lange, Thomas and Wenckebach, Thomas and Lamecker, Hans and Seebaß, Martin and H{\"u}nerbein, Michael and Eulenstein, Sebastian and Schlag, Peter-Michael}, title = {Registration of different phases of contrast-enhanced CT/MRI data for computer-assisted liver surgery planning}, series = {Int. J. Medical Robotics and Computer Assisted Surgery}, volume = {1 (3)}, booktitle = {Int. J. Medical Robotics and Computer Assisted Surgery}, publisher = {Wiley}, doi = {10.1002/rcs.23}, pages = {6 -- 20}, year = {2005}, language = {en} } @inproceedings{SeebassLameckerLangeetal.2003, author = {Seebaß, Martin and Lamecker, Hans and Lange, Thomas and Gellermann, Johanna and Wust, Peter}, title = {A Statistical Shape Model of the Pelvic Bone for Segmentation}, series = {European Society for Hyperthermic Oncology Annual Meeting Proceedings}, booktitle = {European Society for Hyperthermic Oncology Annual Meeting Proceedings}, pages = {91 -- 92}, year = {2003}, language = {en} } @article{HaberlHellZoeckleretal.2004, author = {Haberl, Hannes and Hell, Bertold and Z{\"o}ckler, Maja and Zachow, Stefan and Lamecker, Hans and Sarrafzadeh, Asita and Riecke, B. and Langsch, Wolfgang and Deuflhard, Peter and Bier, J{\"u}rgen and Brock, Mario}, title = {Technical aspects and results of surgery for craniosynostosis}, series = {Zentralblatt f{\"u}r Neurochirurgie}, volume = {65}, journal = {Zentralblatt f{\"u}r Neurochirurgie}, number = {2}, pages = {65 -- 74}, year = {2004}, language = {en} } @inproceedings{LangeWenckebachSeebassetal.2004, author = {Lange, Thomas and Wenckebach, Thomas and Seebaß, Martin and Lamecker, Hans and H{\"u}nerbein, Michael}, title = {Registration of different phases of contrast-enhanced MR data for liver surgery}, series = {3. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie CURAC}, booktitle = {3. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie CURAC}, year = {2004}, language = {en} } @inproceedings{LangeEulensteinHuenerbeinetal.2004, author = {Lange, Thomas and Eulenstein, Sebastian and H{\"u}nerbein, Michael and Lamecker, Hans and Schlag, Peter-Michael}, title = {Augmenting intraoperative 3D ultrasound with preoperative models for navigation in liver surgery}, series = {Proceedings MICCAI}, booktitle = {Proceedings MICCAI}, editor = {Barrilot, Christian}, publisher = {Springer}, pages = {543 -- 541}, year = {2004}, language = {en} } @inproceedings{SeebassLameckerGellermannetal.2004, author = {Seebaß, Martin and Lamecker, Hans and Gellermann, Johanna and Wust, Peter}, title = {The impact of segmentation accuracy on treatment planning for regional hyperthermia}, series = {Proceedings of the 9th International Congress on Hyperthermic Oncology}, booktitle = {Proceedings of the 9th International Congress on Hyperthermic Oncology}, year = {2004}, language = {en} } @inproceedings{EulensteinLangeHuenerbeinetal.2004, author = {Eulenstein, Sebastian and Lange, Thomas and H{\"u}nerbein, Michael and Schlag, Peter and Lamecker, Hans}, title = {Ultrasound based navigation system incorporating preoperative planning for liver surgery}, series = {Proceedings CARS}, volume = {1268}, booktitle = {Proceedings CARS}, publisher = {Elsevier}, doi = {10.1016/j.ics.2004.03.121 target}, pages = {758 -- 763}, year = {2004}, language = {en} } @inproceedings{LangeTunnLameckeretal.2004, author = {Lange, Thomas and Tunn, Per-Ulf and Lamecker, Hans and Scheinemann, Peter and Eulenstein, Sebastian and Schlag, Peter-Michael}, title = {Computerunterst{\"u}tzte Prothesenkonstruktion mittels statistischem Formmodell bei Beckenresektion}, series = {Proceedings BVM, Informatik aktuell}, booktitle = {Proceedings BVM, Informatik aktuell}, editor = {Tolxdorff, Thomas}, publisher = {Springer}, pages = {30 -- 34}, year = {2004}, language = {en} } @inproceedings{LameckerSeebassHegeetal.2004, author = {Lamecker, Hans and Seebaß, Martin and Hege, Hans-Christian and Deuflhard, Peter}, title = {A 3D statistical shape model of the pelvic bone for segmentation}, series = {Proceedings of SPIE - Volume 5370 Medical Imaging 2004}, booktitle = {Proceedings of SPIE - Volume 5370 Medical Imaging 2004}, editor = {Fitzpatrick, J. and Sonka, Milan}, doi = {10.1117/12.534145}, pages = {1341 -- 1351}, year = {2004}, language = {en} } @inproceedings{HegeSchirmacherWesterhoffetal.2002, author = {Hege, Hans-Christian and Schirmacher, Hartmut and Westerhoff, Malte and Lamecker, Hans and Prohaska, Steffen and Zachow, Stefan}, title = {From Image Data to Three-Dimensional Models - Case Studies on the Impact of 3D Patient Models}, series = {Proceedings of the Japan Korea Computer Graphics Conference 2002}, booktitle = {Proceedings of the Japan Korea Computer Graphics Conference 2002}, publisher = {Kanazawa University}, address = {Kanazawa City, Ishikawa, Japan}, year = {2002}, language = {en} } @inproceedings{LameckerLangeSeebassetal.2003, author = {Lamecker, Hans and Lange, Thomas and Seebaß, Martin and Eulenstein, Sebastian and Westerhoff, Malte and Hege, Hans-Christian}, title = {Automatic Segmentation of the Liver for Preoperative Planning of Resections}, series = {Proc. MMVR 2003}, booktitle = {Proc. MMVR 2003}, publisher = {IOS press}, address = {Newport Beach, CA}, pages = {171 -- 173}, year = {2003}, language = {en} } @inproceedings{LangeLameckerEulenstein2002, author = {Lange, Thomas and Lamecker, Hans and Eulenstein, Sebastian}, title = {Automatische Segmentierung von Lebergewebe f{\"u}r die pr{\"a}operative Planung von Resektionen}, series = {1. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- Roboterassistierte Chirugie CURAC}, booktitle = {1. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- Roboterassistierte Chirugie CURAC}, year = {2002}, language = {en} } @inproceedings{LameckerLangeSeebass2002, author = {Lamecker, Hans and Lange, Thomas and Seebaß, Martin}, title = {A Statistical Shape Model for the Liver}, series = {MICCAI 2002}, booktitle = {MICCAI 2002}, publisher = {Springer}, doi = {10.1007/3-540-45787-9_53}, pages = {422 -- 427}, year = {2002}, language = {en} } @inproceedings{LameckerLangeSeebass2003, author = {Lamecker, Hans and Lange, Thomas and Seebaß, Martin}, title = {Erzeugung statistischer 3D-Formmodelle zur Segmentierung medizinischer Bilddaten}, series = {Proc. BVM 2003}, booktitle = {Proc. BVM 2003}, publisher = {Springer}, address = {Erlangen}, pages = {398 -- 403}, year = {2003}, language = {en} } @inproceedings{LangeLameckerSeebass2003, author = {Lange, Thomas and Lamecker, Hans and Seebaß, Martin}, title = {Ein Softwarepaket f{\"u}r die modellbasierte Segmentierung anatomischer Strukturen}, series = {Proc. BVM 2003}, booktitle = {Proc. BVM 2003}, address = {Erlangen}, pages = {111 -- 116}, year = {2003}, language = {en} } @article{EhlkeRammLameckeretal.2013, author = {Ehlke, Moritz and Ramm, Heiko and Lamecker, Hans and Hege, Hans-Christian and Zachow, Stefan}, title = {Fast Generation of Virtual X-ray Images for Reconstruction of 3D Anatomy}, series = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, journal = {IEEE Transactions on Visualization and Computer Graphics}, number = {12}, doi = {10.1109/TVCG.2013.159}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-35928}, pages = {2673 -- 2682}, year = {2013}, language = {en} } @article{RybakKussLameckeretal.2010, author = {Rybak, J{\"u}rgen and Kuß, Anja and Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian and Lienhard, Matthias and Singer, Jochen and Neubert, Kerstin and Menzel, Randolf}, title = {The Digital Bee Brain: Integrating and Managing Neurons in a Common 3D Reference System}, series = {Front. Syst. Neurosci.}, volume = {4}, journal = {Front. Syst. Neurosci.}, number = {30}, doi = {10.3389/fnsys.2010.00030}, year = {2010}, language = {en} } @article{ZachowLameckerZoeckleretal.2009, author = {Zachow, Stefan and Lamecker, Hans and Z{\"o}ckler, Maja and Haberl, Ernst}, title = {Computergest{\"u}tzte Planung zur chirurgischen Korrektur von fr{\"u}hkindlichen Sch{\"a}delfehlbildungen (Craniosynostosen)}, series = {Face 02/09, Int. Mag. of Orofacial Esthetics, Oemus Journale Leipzig}, journal = {Face 02/09, Int. Mag. of Orofacial Esthetics, Oemus Journale Leipzig}, pages = {48 -- 53}, year = {2009}, language = {en} } @misc{GuentherLameckerWeiser, author = {G{\"u}nther, Andreas and Lamecker, Hans and Weiser, Martin}, title = {Direct LDDMM of Discrete Currents with Adaptive Finite Elements}, series = {Proceedings of the Third International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability}, journal = {Proceedings of the Third International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability}, editor = {Pennec, X. and Joshi, S. and Nielsen, M.}, pages = {1 -- 14}, abstract = {We consider Large Deformation Diffeomorphic Metric Mapping of general \$m\$-currents. After stating an optimization algorithm in the function space of admissable morph generating velocity fields, two innovative aspects in this framework are presented and numerically investigated: First, we spatially discretize the velocity field with conforming adaptive finite elements and discuss advantages of this new approach. Second, we directly compute the temporal evolution of discrete \$m\$-current attributes.}, language = {en} } @article{GuentherLameckerWeiser, author = {G{\"u}nther, Andreas and Lamecker, Hans and Weiser, Martin}, title = {Flexible Shape Matching with Finite Element Based LDDMM}, series = {International Journal of Computer Vision}, volume = {105}, journal = {International Journal of Computer Vision}, number = {2}, doi = {10.1007/s11263-012-0599-3}, pages = {128 -- 143}, abstract = {We consider Large Deformation Diffeomorphic Metric Mapping of general \$m\$-currents. After stating an optimization algorithm in the function space of admissable morph generating velocity fields, two innovative aspects in this framework are presented and numerically investigated: First, we spatially discretize the velocity field with conforming adaptive finite elements and discuss advantages of this new approach. Second, we directly compute the temporal evolution of discrete \$m\$-current attributes.}, language = {en} } @article{BernardSalamancaThunbergetal., author = {Bernard, Florian and Salamanca, Luis and Thunberg, Johan and Tack, Alexander and Jentsch, Dennis and Lamecker, Hans and Zachow, Stefan and Hertel, Frank and Goncalves, Jorge and Gemmar, Peter}, title = {Shape-aware Surface Reconstruction from Sparse Data}, series = {arXiv}, journal = {arXiv}, pages = {1602.08425v1}, abstract = {The reconstruction of an object's shape or surface from a set of 3D points is a common topic in materials and life sciences, computationally handled in computer graphics. Such points usually stem from optical or tactile 3D coordinate measuring equipment. Surface reconstruction also appears in medical image analysis, e.g. in anatomy reconstruction from tomographic measurements or the alignment of intra-operative navigation and preoperative planning data. In contrast to mere 3D point clouds, medical imaging yields contextual information on the 3D point data that can be used to adopt prior information on the shape that is to be reconstructed from the measurements. In this work we propose to use a statistical shape model (SSM) as a prior for surface reconstruction. The prior knowledge is represented by a point distribution model (PDM) that is associated with a surface mesh. Using the shape distribution that is modelled by the PDM, we reformulate the problem of surface reconstruction from a probabilistic perspective based on a Gaussian Mixture Model (GMM). In order to do so, the given measurements are interpreted as samples of the GMM. By using mixture components with anisotropic covariances that are oriented according to the surface normals at the PDM points, a surface-based tting is accomplished. By estimating the parameters of the GMM in a maximum a posteriori manner, the reconstruction of the surface from the given measurements is achieved. Extensive experiments suggest that our proposed approach leads to superior surface reconstructions compared to Iterative Closest Point (ICP) methods.}, language = {en} } @inproceedings{BaumMahlowLameckeretal., author = {Baum, Daniel and Mahlow, Kristin and Lamecker, Hans and Zachow, Stefan and M{\"u}ller, Johannes and Hege, Hans-Christian}, title = {The Potential of Surface-based Geometric Morphometrics for Evolutionary Studies: An Example using Dwarf Snakes (Eirenis)}, series = {Abstract in DigitalSpecimen 2014}, booktitle = {Abstract in DigitalSpecimen 2014}, abstract = {Geometric morphometrics plays an important role in evolutionary studies. The state-of-the-art in this field are landmark-based methods. Since the landmarks usually need to be placed manually, only a limited number of landmarks are generally used to represent the shape of an anatomical structure. As a result, shape characteristics that cannot be properly represented by small sets of landmarks are disregarded. In this study, we present a method that is free of this limitation. The method takes into account the whole shape of an anatomical structure, which is represented as a surface, hence the term 'surface-based morphometrics'. Correspondence between two surfaces is established by defining a partitioning of the surfaces into homologous surface patches. The first step for the generation of a surface partitioning is to place landmarks on the surface. Subsequently, the landmarks are connected by curves lying on the surface. The curves, called 'surface paths', might either follow specific anatomical features or they can be geodesics, that is, shortest paths on the surface. One important requirement, however, is that the resulting surface path networks are topologically equivalent across all surfaces. Once the surface path networks have been defined, the surfaces are decomposed into patches according to the path networks. This approach has several advantages. One of them is that we can discretize the surface by as many points as desired. Thus, even fine shape details can be resolved if this is of interest for the study. Since a point discretization is used, another advantage is that well-established analysis methods for landmark-based morphometrics can be utilized. Finally, the shapes can be easily morphed into one another, thereby greatly supporting the understanding of shape changes across all considered specimens. To show the potential of the described method for evolutionary studies of biological specimens, we applied the method to the para-basisphenoid complex of the snake genus Eirenis. By using this anatomical structure as example, we present all the steps that are necessary for surface-based morphometrics, including the segmentation of the para-basisphenoid complex from micro-CT data sets. We also show some first results using statistical analysis as well as classification methods based on the presented technique.}, language = {en} } @misc{LameckerHegeTabelowetal., author = {Lamecker, Hans and Hege, Hans-Christian and Tabelow, Karsten and Polzehl, J{\"o}rg}, title = {Image Processing}, series = {MATHEON - Mathematics for Key Technologies}, journal = {MATHEON - Mathematics for Key Technologies}, editor = {Deuflhard, Peter and et al.,}, publisher = {European Mathematical Society}, doi = {10.4171/137}, pages = {359 -- 376}, language = {en} } @misc{AmbellanTackWilsonetal., author = {Ambellan, Felix and Tack, Alexander and Wilson, Dave and Anglin, Carolyn and Lamecker, Hans and Zachow, Stefan}, title = {Evaluating two methods for Geometry Reconstruction from Sparse Surgical Navigation Data}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-66052}, abstract = {In this study we investigate methods for fitting a Statistical Shape Model (SSM) to intraoperatively acquired point cloud data from a surgical navigation system. We validate the fitted models against the pre-operatively acquired Magnetic Resonance Imaging (MRI) data from the same patients. We consider a cohort of 10 patients who underwent navigated total knee arthroplasty. As part of the surgical protocol the patients' distal femurs were partially digitized. All patients had an MRI scan two months pre-operatively. The MRI data were manually segmented and the reconstructed bone surfaces used as ground truth against which the fit was compared. Two methods were used to fit the SSM to the data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). For both approaches, the difference between model fit and ground truth surface averaged less than 1.7 mm and excellent correspondence with the distal femoral morphology can be demonstrated.}, language = {en} } @article{BernardSalamancaThunbergetal., author = {Bernard, Florian and Salamanca, Luis and Thunberg, Johan and Tack, Alexander and Jentsch, Dennis and Lamecker, Hans and Zachow, Stefan and Hertel, Frank and Goncalves, Jorge and Gemmar, Peter}, title = {Shape-aware Surface Reconstruction from Sparse 3D Point-Clouds}, series = {Medical Image Analysis}, volume = {38}, journal = {Medical Image Analysis}, doi = {10.1016/j.media.2017.02.005}, pages = {77 -- 89}, abstract = {The reconstruction of an object's shape or surface from a set of 3D points plays an important role in medical image analysis, e.g. in anatomy reconstruction from tomographic measurements or in the process of aligning intra-operative navigation and preoperative planning data. In such scenarios, one usually has to deal with sparse data, which significantly aggravates the problem of reconstruction. However, medical applications often provide contextual information about the 3D point data that allow to incorporate prior knowledge about the shape that is to be reconstructed. To this end, we propose the use of a statistical shape model (SSM) as a prior for surface reconstruction. The SSM is represented by a point distribution model (PDM), which is associated with a surface mesh. Using the shape distribution that is modelled by the PDM, we formulate the problem of surface reconstruction from a probabilistic perspective based on a Gaussian Mixture Model (GMM). In order to do so, the given points are interpreted as samples of the GMM. By using mixture components with anisotropic covariances that are "oriented" according to the surface normals at the PDM points, a surface-based fitting is accomplished. Estimating the parameters of the GMM in a maximum a posteriori manner yields the reconstruction of the surface from the given data points. We compare our method to the extensively used Iterative Closest Points method on several different anatomical datasets/SSMs (brain, femur, tibia, hip, liver) and demonstrate superior accuracy and robustness on sparse data.}, language = {en} } @inproceedings{MukhopadhyayMorilloZachowetal., author = {Mukhopadhyay, Anirban and Morillo, Oscar and Zachow, Stefan and Lamecker, Hans}, title = {Robust and Accurate Appearance Models Based on Joint Dictionary Learning Data from the Osteoarthritis Initiative}, series = {Lecture Notes in Computer Science, Patch-Based Techniques in Medical Imaging. Patch-MI 2016}, volume = {9993}, booktitle = {Lecture Notes in Computer Science, Patch-Based Techniques in Medical Imaging. Patch-MI 2016}, doi = {10.1007/978-3-319-47118-1_4}, pages = {25 -- 33}, abstract = {Deformable model-based approaches to 3D image segmentation have been shown to be highly successful. Such methodology requires an appearance model that drives the deformation of a geometric model to the image data. Appearance models are usually either created heuristically or through supervised learning. Heuristic methods have been shown to work effectively in many applications but are hard to transfer from one application (imaging modality/anatomical structure) to another. On the contrary, supervised learning approaches can learn patterns from a collection of annotated training data. In this work, we show that the supervised joint dictionary learning technique is capable of overcoming the traditional drawbacks of the heuristic approaches. Our evaluation based on two different applications (liver/CT and knee/MR) reveals that our approach generates appearance models, which can be used effectively and efficiently in a deformable model-based segmentation framework.}, language = {en} } @incollection{LameckerZachow, author = {Lamecker, Hans and Zachow, Stefan}, title = {Statistical Shape Modeling of Musculoskeletal Structures and Its Applications}, series = {Computational Radiology for Orthopaedic Interventions}, volume = {23}, booktitle = {Computational Radiology for Orthopaedic Interventions}, publisher = {Springer}, isbn = {978-3-319-23481-6}, doi = {10.1007/978-3-319-23482-3}, pages = {1 -- 23}, abstract = {Statistical shape models (SSM) describe the shape variability contained in a given population. They are able to describe large populations of complex shapes with few degrees of freedom. This makes them a useful tool for a variety of tasks that arise in computer-aided madicine. In this chapter we are going to explain the basic methodology of SSMs and present a variety of examples, where SSMs have been successfully applied.}, language = {en} } @inproceedings{RammVictoriaMorilloTodtetal.2013, author = {Ramm, Heiko and Victoria Morillo, Oscar Salvador and Todt, Ingo and Schirmacher, Hartmut and Ernst, Arneborg and Zachow, Stefan and Lamecker, Hans}, title = {Visual Support for Positioning Hearing Implants}, series = {Proceedings of the 12th annual meeting of the CURAC society}, booktitle = {Proceedings of the 12th annual meeting of the CURAC society}, editor = {Freysinger, Wolfgang}, pages = {116 -- 120}, year = {2013}, language = {en} } @article{KainmuellerLameckerHelleretal.2013, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Heller, Markus O. and Weber, Britta and Hege, Hans-Christian and Zachow, Stefan}, title = {Omnidirectional Displacements for Deformable Surfaces}, series = {Medical Image Analysis}, volume = {17}, journal = {Medical Image Analysis}, number = {4}, publisher = {Elsevier}, doi = {10.1016/j.media.2012.11.006}, pages = {429 -- 441}, year = {2013}, language = {en} } @inproceedings{vonBergDworzakKlinderetal.2011, author = {von Berg, Jens and Dworzak, Jalda and Klinder, Tobias and Manke, Dirk and Lamecker, Hans and Zachow, Stefan and Lorenz, Cristian}, title = {Temporal Subtraction of Chest Radiographs Compensating Pose Differences}, series = {SPIE Medical Imaging}, booktitle = {SPIE Medical Imaging}, year = {2011}, language = {en} } @inproceedings{BindernagelKainmuellerSeimetal.2011, author = {Bindernagel, Matthias and Kainm{\"u}ller, Dagmar and Seim, Heiko and Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian}, title = {An Articulated Statistical Shape Model of the Human Knee}, series = {Bildverarbeitung f{\"u}r die Medizin 2011}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2011}, publisher = {Springer}, doi = {10.1007/978-3-642-19335-4_14}, pages = {59 -- 63}, year = {2011}, language = {en} } @inproceedings{KahntGallowaySeimetal.2011, author = {Kahnt, Max and Galloway, Francis and Seim, Heiko and Lamecker, Hans and Taylor, Mark and Zachow, Stefan}, title = {Robust and Intuitive Meshing of Bone-Implant Compounds}, series = {CURAC}, booktitle = {CURAC}, address = {Magdeburg}, pages = {71 -- 74}, year = {2011}, language = {en} } @inproceedings{PapazovDercksenLameckeretal.2008, author = {Papazov, Chavdar and Dercksen, Vincent J. and Lamecker, Hans and Hege, Hans-Christian}, title = {Visualizing morphogenesis and growth by temporal interpolation of surface-based 3D atlases}, series = {Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging}, booktitle = {Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging}, doi = {10.1109/ISBI.2008.4541123}, pages = {824 -- 827}, year = {2008}, language = {en} } @article{SahnerWeberLameckeretal.2008, author = {Sahner, Jan and Weber, Britta and Lamecker, Hans and Prohaska, Steffen}, title = {Extraction of feature Lines on surface meshes based on discrete Morse theory}, series = {Computer Graphics Forum}, volume = {27}, journal = {Computer Graphics Forum}, number = {3}, address = {Eindhoven, Netherlands}, doi = {10.1111/j.1467-8659.2008.01202.x}, pages = {735 -- 742}, year = {2008}, language = {en} } @inproceedings{KainmuellerLameckerZachowetal.2008, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian}, title = {Coupling Deformable Models for Multi-object Segmentation}, series = {Proc. Int. Symp. on Computational Models for Biomedical Simulation (ISBMS)}, booktitle = {Proc. Int. Symp. on Computational Models for Biomedical Simulation (ISBMS)}, doi = {10.1007/978-3-540-70521-5_8}, pages = {69 -- 78}, year = {2008}, language = {en} } @inproceedings{KainmuellerLameckerZachowetal.2008, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan and Heller, Markus O. and Hege, Hans-Christian}, title = {Multi-Object Segmentation with Coupled Deformable Models}, series = {Proc. Medical Image Understanding and Analysis}, booktitle = {Proc. Medical Image Understanding and Analysis}, pages = {34 -- 38}, year = {2008}, language = {en} } @inproceedings{SeimKainmuellerKussetal.2008, author = {Seim, Heiko and Kainm{\"u}ller, Dagmar and Kuss, Anja and Lamecker, Hans and Zachow, Stefan and Menzel, Randolf and Rybak, Juergen}, title = {Model-based autosegmentation of the central brain of the honeybee, Apis mellifera, using active statistical shape models}, series = {Proc. 1st INCF Congress of Neuroinformatics: Databasing and Modeling the Brain}, booktitle = {Proc. 1st INCF Congress of Neuroinformatics: Databasing and Modeling the Brain}, doi = {10.3389/conf.neuro.11.2008.01.064}, year = {2008}, language = {en} } @inproceedings{DworzakLameckervonBergetal.2008, author = {Dworzak, Jalda and Lamecker, Hans and von Berg, Jens and Klinder, Tobias and Lorenz, Cristian and Kainm{\"u}ller, Dagmar and Seim, Heiko and Hege, Hans-Christian and Zachow, Stefan}, title = {Towards model-based 3-D reconstruction of the human rib cage from radiographs}, series = {Proc. 7. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie (CURAC)}, booktitle = {Proc. 7. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer-Roboterassistierte Chirurgie (CURAC)}, pages = {193 -- 196}, year = {2008}, language = {en} } @inproceedings{SeimKainmuellerHelleretal.2008, author = {Seim, Heiko and Kainm{\"u}ller, Dagmar and Heller, Markus O. and Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian}, title = {Automatic Segmentation of the Pelvic Bones from CT Data Based on a Statistical Shape Model}, series = {Eurographics Workshop on Visual Computing for Biomedicine (VCBM)}, booktitle = {Eurographics Workshop on Visual Computing for Biomedicine (VCBM)}, address = {Delft, Netherlands}, pages = {93 -- 100}, year = {2008}, language = {en} } @article{LameckerPennec2010, author = {Lamecker, Hans and Pennec, Xavier}, title = {Atlas to Image-with-Tumor Registration based on Demons and Deformation Inpainting}, series = {Proc. MICCAI Workshop on Computational Imaging Biomarkers for Tumors - From Qualitative to Quantitative (CIBT'2010)}, journal = {Proc. MICCAI Workshop on Computational Imaging Biomarkers for Tumors - From Qualitative to Quantitative (CIBT'2010)}, address = {Beijing, China}, year = {2010}, language = {en} } @inproceedings{SeimKainmuellerLameckeretal.2010, author = {Seim, Heiko and Kainm{\"u}ller, Dagmar and Lamecker, Hans and Bindernagel, Matthias and Malinowski, Jana and Zachow, Stefan}, title = {Model-based Auto-Segmentation of Knee Bones and Cartilage in MRI Data}, series = {Proc. MICCAI Workshop Medical Image Analysis for the Clinic}, booktitle = {Proc. MICCAI Workshop Medical Image Analysis for the Clinic}, editor = {v. Ginneken, B.}, pages = {215 -- 223}, year = {2010}, language = {en} } @misc{EhlkeRammLameckeretal.2012, author = {Ehlke, Moritz and Ramm, Heiko and Lamecker, Hans and Zachow, Stefan}, title = {Efficient projection and deformation of volumetric shape and intensity models for accurate simulation of X-ray images}, series = {Eurographics Workshop on Visual Computing for Biomedicine (NVIDIA best poster award)}, journal = {Eurographics Workshop on Visual Computing for Biomedicine (NVIDIA best poster award)}, year = {2012}, language = {en} } @inproceedings{KahntRammLameckeretal.2012, author = {Kahnt, Max and Ramm, Heiko and Lamecker, Hans and Zachow, Stefan}, title = {Feature-Preserving, Multi-Material Mesh Generation using Hierarchical Oracles}, series = {Proc. MICCAI Workshop on Mesh Processing in Medical Image Analysis (MeshMed)}, volume = {7599}, booktitle = {Proc. MICCAI Workshop on Mesh Processing in Medical Image Analysis (MeshMed)}, editor = {Levine, Joshua A. and Paulsen, Rasmus R. and Zhang, Yongjie}, pages = {101 -- 111}, year = {2012}, language = {en} } @article{KainmuellerLameckerSeimetal.2009, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Seim, Heiko and Zachow, Stefan}, title = {Multi-object segmentation of head bones}, series = {MIDAS Journal}, journal = {MIDAS Journal}, year = {2009}, language = {en} } @inproceedings{SeimKainmuellerLameckeretal.2009, author = {Seim, Heiko and Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan}, title = {A System for Unsupervised Extraction of Orthopaedic Parameters from CT Data}, series = {GI Workshop Softwareassistenten - Computerunterst{\"u}tzung f{\"u}r die medizinische Diagnose und Therapieplanung}, booktitle = {GI Workshop Softwareassistenten - Computerunterst{\"u}tzung f{\"u}r die medizinische Diagnose und Therapieplanung}, address = {L{\"u}beck, Germany}, pages = {1328 -- 1337}, year = {2009}, language = {en} } @inproceedings{LameckerMansiRelanetal.2009, author = {Lamecker, Hans and Mansi, Tomaso and Relan, Jatin and Billet, Florence and Sermesant, Maxime and Ayache, Nicholas and Delingette, Herv{\´e}}, title = {Adaptive Tetrahedral Meshing for Personalized Cardiac Simulations}, series = {Proc. MICCAI Workshop on Cardiovascular Interventional Imaging and Biophysical Modelling (CI2BM)}, booktitle = {Proc. MICCAI Workshop on Cardiovascular Interventional Imaging and Biophysical Modelling (CI2BM)}, pages = {149 -- 158}, year = {2009}, language = {en} } @inproceedings{KainmuellerLameckerSeimetal.2009, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Seim, Heiko and Zinser, Max and Zachow, Stefan}, title = {Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data}, series = {Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI)}, booktitle = {Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI)}, editor = {Yang, Guang-Zhong and J. Hawkes, David and Rueckert, Daniel and Noble, J. Alison and J. Taylor, Chris}, address = {London, UK}, pages = {76 -- 83}, year = {2009}, language = {en} } @inproceedings{KainmuellerLameckerZachowetal.2009, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian}, title = {An Articulated Statistical Shape Model for Accurate Hip Joint Segmentation}, series = {EBMC 2009. Int. Conf. of the IEEE Eng. in Med. and Biol. Society (EMBC)}, booktitle = {EBMC 2009. Int. Conf. of the IEEE Eng. in Med. and Biol. Society (EMBC)}, address = {Minneapolis, USA}, pages = {6345 -- 6351}, year = {2009}, language = {en} } @inproceedings{HeimannChungLameckeretal.2009, author = {Heimann, Tobias and Chung, Fran{\c{c}}ois and Lamecker, Hans and Delingette, Herv{\´e}}, title = {Subject-Specific Ligament Models: Towards Real-Time Simulation of the Knee Joint}, series = {Proc. Computational Biomechanics for Medicine IV Workshop}, booktitle = {Proc. Computational Biomechanics for Medicine IV Workshop}, publisher = {Springer New York}, doi = {10.1007/978-1-4419-5874-7}, pages = {107 -- 119}, year = {2009}, language = {en} } @article{KainmuellerLameckerZachow2009, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Zachow, Stefan}, title = {Multi-object Segmentation with Coupled Deformable Models}, series = {Annals of the British Machine Vision Association (BMVA)}, volume = {5}, journal = {Annals of the British Machine Vision Association (BMVA)}, pages = {1 -- 10}, year = {2009}, language = {en} } @inproceedings{ZilskeLameckerZachow2008, author = {Zilske, Michael and Lamecker, Hans and Zachow, Stefan}, title = {Adaptive Remeshing of Non-Manifold Surfaces}, series = {Eurographics 2008 Annex to the Conf. Proc.}, booktitle = {Eurographics 2008 Annex to the Conf. Proc.}, pages = {207 -- 211}, year = {2008}, language = {en} } @inproceedings{SeimLameckerZachow2008, author = {Seim, Heiko and Lamecker, Hans and Zachow, Stefan}, title = {Segmentation of Bony Structures with Ligament Attachment Sites}, series = {Bildverarbeitung f{\"u}r die Medizin 2008}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2008}, publisher = {Springer}, doi = {10.1007/978-3-540-78640-5_42}, pages = {207 -- 211}, year = {2008}, language = {en} } @misc{LangeLameckerHuenerbeinetal.2008, author = {Lange, Thomas and Lamecker, Hans and H{\"u}nerbein, Michael and Eulenstein, Sebastian and Beller, Sigfried and Schlag, Peter}, title = {Validation Metrics for Non-Rigid Registration of Medical Images containing Vessel Trees}, publisher = {Springer}, doi = {10.1007/978-3-540-78640-5_17}, pages = {82 -- 86}, year = {2008}, language = {en} } @inproceedings{KainmuellerLameckerSeimetal.2010, author = {Kainm{\"u}ller, Dagmar and Lamecker, Hans and Seim, Heiko and Zachow, Stefan and Hege, Hans-Christian}, title = {Improving Deformable Surface Meshes through Omni-directional Displacements and MRFs}, series = {Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI)}, volume = {6361}, booktitle = {Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI)}, editor = {Navab, Tianzi and P. W. Pluim, Josien and Viergever, Max}, publisher = {Springer}, doi = {10.1007/978-3-642-15705-9_28}, pages = {227 -- 234}, year = {2010}, language = {en} } @inproceedings{ZachowKubiackMalinowskietal.2010, author = {Zachow, Stefan and Kubiack, Kim and Malinowski, Jana and Lamecker, Hans and Essig, Harald and Gellrich, Nils-Claudius}, title = {Modellgest{\"u}tzte chirurgische Rekonstruktion komplexer Mittelgesichtsfrakturen}, series = {Proc. BMT, Biomed Tech 2010}, volume = {55 (Suppl 1)}, booktitle = {Proc. BMT, Biomed Tech 2010}, publisher = {Walter de Gruyter-Verlag}, pages = {107 -- 108}, year = {2010}, language = {de} } @inproceedings{LameckerKainmuellerSeimetal.2010, author = {Lamecker, Hans and Kainm{\"u}ller, Dagmar and Seim, Heiko and Zachow, Stefan}, title = {Automatische 3D Rekonstruktion des Unterkiefers und der Mandibul{\"a}rnerven auf Basis dentaler Bildgebung}, series = {Proc. BMT, Biomed Tech}, volume = {55 (Suppl. 1)}, booktitle = {Proc. BMT, Biomed Tech}, publisher = {Walter de Gruyter-Verlag}, pages = {35 -- 36}, year = {2010}, language = {en} } @article{DworzakLameckervonBergetal.2010, author = {Dworzak, Jalda and Lamecker, Hans and von Berg, Jens and Klinder, Tobias and Lorenz, Cristian and Kainm{\"u}ller, Dagmar and Seim, Heiko and Hege, Hans-Christian and Zachow, Stefan}, title = {3D Reconstruction of the Human Rib Cage from 2D Projection Images using a Statistical Shape Model}, series = {Int. J. Comput. Assist. Radiol. Surg.}, volume = {5}, journal = {Int. J. Comput. Assist. Radiol. Surg.}, number = {2}, publisher = {Springer}, issn = {1861-6410}, doi = {10.1007/s11548-009-0390-2}, pages = {111 -- 124}, year = {2010}, language = {en} } @misc{KamerNoserLameckeretal.2006, author = {Kamer, Lukas and Noser, Hansrudi and Lamecker, Hans and Zachow, Stefan and Wittmers, Antonia and Kaup, Thomas and Schramm, Alexander and Hammer, Beat}, title = {Three-dimensional statistical shape analysis - A useful tool for developing a new type of orbital implant?}, publisher = {AO Development Institute, New Products Brochure 2/06}, pages = {20 -- 21}, year = {2006}, language = {en} } @inproceedings{LameckerWenckebachHege2006, author = {Lamecker, Hans and Wenckebach, Thomas and Hege, Hans-Christian}, title = {Atlas-based 3D-shape reconstruction from x-ray images}, series = {Proc. Int. Conf. of Pattern Recognition (ICPR2006)}, volume = {Volume I}, booktitle = {Proc. Int. Conf. of Pattern Recognition (ICPR2006)}, publisher = {IEEE Computer Society}, doi = {10.1109/ICPR.2006.279}, pages = {371 -- 374}, year = {2006}, language = {en} } @article{LangeHuenerbeinEulensteinetal.2007, author = {Lange, Thomas and H{\"u}nerbein, Michael and Eulenstein, Sebastian and Beller, Sigfried and Schlag, Peter and Lamecker, Hans}, title = {A Distance Measure for Non-Rigid Registration of Geometrical Models to Intensity Data}, series = {Int. J. Computer Assisted Radiology and Surgery}, volume = {2, Suppl. 1}, journal = {Int. J. Computer Assisted Radiology and Surgery}, publisher = {Springer}, pages = {204 -- 206}, year = {2007}, language = {en} } @inproceedings{NeubertLameckerHegeetal.2007, author = {Neubert, Kerstin and Lamecker, Hans and Hege, Hans-Christian and Menzel, Randolf and Rybak, J{\"u}rgen}, title = {Model-based autosegmentation of brain structures in the honeybee using statistical shape models}, series = {Proc. 8th Int. Congr. of Neuroethology (ICN)}, booktitle = {Proc. 8th Int. Congr. of Neuroethology (ICN)}, year = {2007}, language = {en} } @article{KainmuellerLangeLamecker2007, author = {Kainm{\"u}ller, Dagmar and Lange, Thomas and Lamecker, Hans}, title = {Shape constrained automatic segmentation of the liver based on a heuristic intensity model}, series = {Proc. MICCAI Workshop 3D Segmentation in the Clinic}, journal = {Proc. MICCAI Workshop 3D Segmentation in the Clinic}, pages = {109 -- 116}, year = {2007}, language = {en} } @article{LameckerKamerWittmersetal.2007, author = {Lamecker, Hans and Kamer, Lukas and Wittmers, Antonia and Zachow, Stefan and Kaup, Thomas and Schramm, Alexander and Noser, Hansrudi and Hammer, Beat}, title = {A method for the three-dimensional statistical shape analysis of the bony orbit}, series = {Proc. Computer Aided Surgery around the Head}, journal = {Proc. Computer Aided Surgery around the Head}, pages = {94 -- 97}, year = {2007}, language = {en} } @inproceedings{LangeLameckerHuenerbeinetal.2007, author = {Lange, Thomas and Lamecker, Hans and H{\"u}nerbein, Michael and Eulenstein, Sebastian and Beller, Sigfried and Schlag, Peter}, title = {A new class of distance measures for registration of tubular models to image data}, series = {Proc. Bildverarbeitung f{\"u}r die Medizin (BVM)}, booktitle = {Proc. Bildverarbeitung f{\"u}r die Medizin (BVM)}, editor = {Horsch, A.}, publisher = {Springer}, doi = {10.1007/978-3-540-71091-2_21}, pages = {101 -- 105}, year = {2007}, language = {en} } @inproceedings{ZachowLameckerElsholtzetal.2005, author = {Zachow, Stefan and Lamecker, Hans and Elsholtz, Barbara and Stiller, Michael}, title = {Reconstruction of mandibular dysplasia using a statistical 3D shape model}, series = {Proc. Computer Assisted Radiology and Surgery (CARS)}, booktitle = {Proc. Computer Assisted Radiology and Surgery (CARS)}, address = {Berlin, Germany}, doi = {10.1016/j.ics.2005.03.339}, pages = {1238 -- 1243}, year = {2005}, language = {en} } @inproceedings{WenckebachLameckerHege2005, author = {Wenckebach, Thomas and Lamecker, Hans and Hege, Hans-Christian}, title = {Capturing anatomical shape variability using B-spline registration}, series = {Information Processing in Medical Imaging: 19th International Conference (IPMI 2005)}, volume = {3565/2005}, booktitle = {Information Processing in Medical Imaging: 19th International Conference (IPMI 2005)}, editor = {Christensen, Gary and Sonka, Milan}, publisher = {Springer-Verlag GmbH}, address = {Glenwood Springs, CO, USA}, doi = {10.1007/b137723}, pages = {578 -- 590}, year = {2005}, language = {en} } @article{LameckerZachowHaberletal.2005, author = {Lamecker, Hans and Zachow, Stefan and Haberl, Hannes and Stiller, Michael}, title = {Medical applications for statistical shape models}, series = {Computer Aided Surgery around the Head, Fortschritt-Berichte VDI - Biotechnik/Medizintechnik}, volume = {17 (258)}, journal = {Computer Aided Surgery around the Head, Fortschritt-Berichte VDI - Biotechnik/Medizintechnik}, pages = {61}, year = {2005}, language = {en} } @inproceedings{LameckerWenckebachHegeetal.2006, author = {Lamecker, Hans and Wenckebach, Thomas and Hege, Hans-Christian and N. Duda, Georg and Heller, Markus}, title = {Atlas-basierte 3D-Rekonstruktion des Beckens aus 2D-Projektionsbildern}, series = {Bildverarbeitung f{\"u}r die Medizin 2006: Algorithmen - Systeme - Anwendungen}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2006: Algorithmen - Systeme - Anwendungen}, publisher = {Springer Berlin Heidelberg}, doi = {10.1007/3-540-32137-3_6}, pages = {26 -- 30}, year = {2006}, language = {en} } @article{LameckerZachowWittmersetal.2006, author = {Lamecker, Hans and Zachow, Stefan and Wittmers, Antonia and Weber, Britta and Hege, Hans-Christian and Elsholtz, Barbara and Stiller, Michael}, title = {Automatic segmentation of mandibles in low-dose CT-data}, series = {Int. J. Computer Assisted Radiology and Surgery}, volume = {1(1)}, journal = {Int. J. Computer Assisted Radiology and Surgery}, pages = {393 -- 395}, year = {2006}, language = {en} } @article{LameckerZachowHegeetal.2006, author = {Lamecker, Hans and Zachow, Stefan and Hege, Hans-Christian and Z{\"o}ckler, Maja}, title = {Surgical treatment of craniosynostosis based on a statistical 3D-shape model}, series = {Int. J. Computer Assisted Radiology and Surgery}, volume = {1(1)}, journal = {Int. J. Computer Assisted Radiology and Surgery}, doi = {10.1007/s11548-006-0024-x}, pages = {253 -- 254}, year = {2006}, language = {en} } @article{ZachowLameckerElsholtzetal.2006, author = {Zachow, Stefan and Lamecker, Hans and Elsholtz, Barbara and Stiller, Michael}, title = {Is the course of the mandibular nerve deducible from the shape of the mandible?}, series = {Int. J. of Computer Assisted Radiology and Surgery}, journal = {Int. J. of Computer Assisted Radiology and Surgery}, publisher = {Springer}, pages = {415 -- 417}, year = {2006}, language = {en} } @inproceedings{EstacioEhlkeTacketal., author = {Estacio, Laura and Ehlke, Moritz and Tack, Alexander and Castro-Gutierrez, Eveling and Lamecker, Hans and Mora, Rensso and Zachow, Stefan}, title = {Unsupervised Detection of Disturbances in 2D Radiographs}, series = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)}, booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)}, doi = {10.1109/ISBI48211.2021.9434091}, pages = {367 -- 370}, abstract = {We present a method based on a generative model for detection of disturbances such as prosthesis, screws, zippers, and metals in 2D radiographs. The generative model is trained in an unsupervised fashion using clinical radiographs as well as simulated data, none of which contain disturbances. Our approach employs a latent space consistency loss which has the benefit of identifying similarities, and is enforced to reconstruct X-rays without disturbances. In order to detect images with disturbances, an anomaly score is computed also employing the Frechet distance between the input X-ray and the reconstructed one using our generative model. Validation was performed using clinical pelvis radiographs. We achieved an AUC of 0.77 and 0.83 with clinical and synthetic data, respectively. The results demonstrated a good accuracy of our method for detecting outliers as well as the advantage of utilizing synthetic data.}, language = {en} } @article{PimentelSzengelEhlkeetal., author = {Pimentel, Pedro and Szengel, Angelika and Ehlke, Moritz and Lamecker, Hans and Zachow, Stefan and Estacio, Laura and Doenitz, Christian and Ramm, Heiko}, title = {Automated Virtual Reconstruction of Large Skull Defects using Statistical Shape Models and Generative Adversarial Networks}, series = {Towards the Automatization of Cranial Implant Design in Cranioplasty}, volume = {12439}, journal = {Towards the Automatization of Cranial Implant Design in Cranioplasty}, editor = {Li, Jianning and Egger, Jan}, edition = {1}, publisher = {Springer International Publishing}, doi = {10.1007/978-3-030-64327-0_3}, pages = {16 -- 27}, abstract = {We present an automated method for extrapolating missing regions in label data of the skull in an anatomically plausible manner. The ultimate goal is to design patient-speci� c cranial implants for correcting large, arbitrarily shaped defects of the skull that can, for example, result from trauma of the head. Our approach utilizes a 3D statistical shape model (SSM) of the skull and a 2D generative adversarial network (GAN) that is trained in an unsupervised fashion from samples of healthy patients alone. By � tting the SSM to given input labels containing the skull defect, a First approximation of the healthy state of the patient is obtained. The GAN is then applied to further correct and smooth the output of the SSM in an anatomically plausible manner. Finally, the defect region is extracted using morphological operations and subtraction between the extrapolated healthy state of the patient and the defective input labels. The method is trained and evaluated based on data from the MICCAI 2020 AutoImplant challenge. It produces state-of-the art results on regularly shaped cut-outs that were present in the training and testing data of the challenge. Furthermore, due to unsupervised nature of the approach, the method generalizes well to previously unseen defects of varying shapes that were only present in the hidden test dataset.}, language = {en} } @misc{AmbellanLameckervonTycowiczetal., author = {Ambellan, Felix and Lamecker, Hans and von Tycowicz, Christoph and Zachow, Stefan}, title = {Statistical Shape Models - Understanding and Mastering Variation in Anatomy}, issn = {1438-0064}, doi = {10.1007/978-3-030-19385-0_5}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-72699}, abstract = {In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digital anatomy atlases will not only show a static (average) anatomy but also its normal or pathological variation in three or even four dimensions, hence, illustrating growth and/or disease progression. Statistical Shape Models (SSMs) are geometric models that describe a collection of semantically similar objects in a very compact way. SSMs represent an average shape of many three-dimensional objects as well as their variation in shape. The creation of SSMs requires a correspondence mapping, which can be achieved e.g. by parameterization with a respective sampling. If a corresponding parameterization over all shapes can be established, variation between individual shape characteristics can be mathematically investigated. We will explain what Statistical Shape Models are and how they are constructed. Extensions of Statistical Shape Models will be motivated for articulated coupled structures. In addition to shape also the appearance of objects will be integrated into the concept. Appearance is a visual feature independent of shape that depends on observers or imaging techniques. Typical appearances are for instance the color and intensity of a visual surface of an object under particular lighting conditions, or measurements of material properties with computed tomography (CT) or magnetic resonance imaging (MRI). A combination of (articulated) statistical shape models with statistical models of appearance lead to articulated Statistical Shape and Appearance Models (a-SSAMs).After giving various examples of SSMs for human organs, skeletal structures, faces, and bodies, we will shortly describe clinical applications where such models have been successfully employed. Statistical Shape Models are the foundation for the analysis of anatomical cohort data, where characteristic shapes are correlated to demographic or epidemiologic data. SSMs consisting of several thousands of objects offer, in combination with statistical methods ormachine learning techniques, the possibility to identify characteristic clusters, thus being the foundation for advanced diagnostic disease scoring.}, language = {en} } @article{HildebrandtBrueningSchmidtetal., author = {Hildebrandt, Thomas and Bruening, Jan Joris and Schmidt, Nora Laura and Lamecker, Hans and Heppt, Werner and Zachow, Stefan and Goubergrits, Leonid}, title = {The Healthy Nasal Cavity - Characteristics of Morphology and Related Airflow Based on a Statistical Shape Model Viewed from a Surgeon's Perspective}, series = {Facial Plastic Surgery}, volume = {35}, journal = {Facial Plastic Surgery}, number = {1}, doi = {10.1055/s-0039-1677721}, pages = {9 -- 13}, abstract = {Functional surgery on the nasal framework requires referential criteria to objectively assess nasal breathing for indication and follow-up. Thismotivated us to generate amean geometry of the nasal cavity based on a statistical shape model. In this study, the authors could demonstrate that the introduced nasal cavity's mean geometry features characteristics of the inner shape and airflow, which are commonly observed in symptom-free subjects. Therefore, the mean geometry might serve as a reference-like model when one considers qualitative aspects. However, to facilitate quantitative considerations and statistical inference, further research is necessary. Additionally, the authorswere able to obtain details about the importance of the isthmus nasi and the inferior turbinate for the intranasal airstream.}, language = {en} } @article{HildebrandtBrueningLameckeretal., author = {Hildebrandt, Thomas and Bruening, Jan Joris and Lamecker, Hans and Zachow, Stefan and Heppt, Werner and Schmidt, Nora and Goubergrits, Leonid}, title = {Digital Analysis of Nasal Airflow Facilitating Decision Support in Rhinosurgery}, series = {Facial Plastic Surgery}, volume = {35}, journal = {Facial Plastic Surgery}, number = {1}, doi = {10.1055/s-0039-1677720}, pages = {1 -- 8}, abstract = {Successful functional surgery on the nasal framework requires reliable and comprehensive diagnosis. In this regard, the authors introduce a new methodology: Digital Analysis of Nasal Airflow (diANA). It is based on computational fluid dynamics, a statistical shape model of the healthy nasal cavity and rhinologic expertise. diANA necessitates an anonymized tomographic dataset of the paranasal sinuses including the complete nasal cavity and, when available, clinical information. The principle of diANA is to compare the morphology and the respective airflow of an individual nose with those of a reference. This enablesmorphometric aberrations and consecutive flow field anomalies to localize and quantify within a patient's nasal cavity. Finally, an elaborated expert opinion with instructive visualizations is provided. Using diANA might support surgeons in decision-making, avoiding unnecessary surgery, gaining more precision, and target-orientation for indicated operations.}, language = {en} } @article{HettichSchierjottSchillingetal., author = {Hettich, G. and Schierjott, R. A. and Schilling, C. and Maas, A. and Ramm, Heiko and Bindernagel, Matthias and Lamecker, Hans and Grupp, T. M.}, title = {Validation of a Statistical Shape Model for Acetabular Bone Defect Analysis}, series = {ISTA 2018 London Abstract Book}, journal = {ISTA 2018 London Abstract Book}, abstract = {Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to apply them in pre-clinical testing, implant development and pre-operative planning. By reconstructing the native situation of a defect pelvis using a Statistical Shape Model (SSM), a more quantitative analysis of the bone defects could be performed. The aim of this study is to develop such a SSM and to validate its accuracy using relevant clinical scenarios and parameters.}, language = {en} } @incollection{AmbellanLameckervonTycowiczetal., author = {Ambellan, Felix and Lamecker, Hans and von Tycowicz, Christoph and Zachow, Stefan}, title = {Statistical Shape Models - Understanding and Mastering Variation in Anatomy}, series = {Biomedical Visualisation}, volume = {3}, booktitle = {Biomedical Visualisation}, number = {1156}, editor = {Rea, Paul M.}, edition = {1}, publisher = {Springer Nature Switzerland AG}, isbn = {978-3-030-19384-3}, doi = {10.1007/978-3-030-19385-0_5}, pages = {67 -- 84}, abstract = {In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digital anatomy atlases will not only show a static (average) anatomy but also its normal or pathological variation in three or even four dimensions, hence, illustrating growth and/or disease progression. Statistical Shape Models (SSMs) are geometric models that describe a collection of semantically similar objects in a very compact way. SSMs represent an average shape of many three-dimensional objects as well as their variation in shape. The creation of SSMs requires a correspondence mapping, which can be achieved e.g. by parameterization with a respective sampling. If a corresponding parameterization over all shapes can be established, variation between individual shape characteristics can be mathematically investigated. We will explain what Statistical Shape Models are and how they are constructed. Extensions of Statistical Shape Models will be motivated for articulated coupled structures. In addition to shape also the appearance of objects will be integrated into the concept. Appearance is a visual feature independent of shape that depends on observers or imaging techniques. Typical appearances are for instance the color and intensity of a visual surface of an object under particular lighting conditions, or measurements of material properties with computed tomography (CT) or magnetic resonance imaging (MRI). A combination of (articulated) statistical shape models with statistical models of appearance lead to articulated Statistical Shape and Appearance Models (a-SSAMs).After giving various examples of SSMs for human organs, skeletal structures, faces, and bodies, we will shortly describe clinical applications where such models have been successfully employed. Statistical Shape Models are the foundation for the analysis of anatomical cohort data, where characteristic shapes are correlated to demographic or epidemiologic data. SSMs consisting of several thousands of objects offer, in combination with statistical methods ormachine learning techniques, the possibility to identify characteristic clusters, thus being the foundation for advanced diagnostic disease scoring.}, language = {en} } @article{BrueningHildebrandtHepptetal., author = {Br{\"u}ning, Jan and Hildebrandt, Thomas and Heppt, Werner and Schmidt, Nora and Lamecker, Hans and Szengel, Angelika and Amiridze, Natalja and Ramm, Heiko and Bindernagel, Matthias and Zachow, Stefan and Goubergrits, Leonid}, title = {Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity}, series = {Scientific Reports}, volume = {3755}, journal = {Scientific Reports}, number = {10}, doi = {10.1038/s41598-020-60755-3}, abstract = {This study's objective was the generation of a standardized geometry of the healthy nasal cavity. An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the nasal resistance, wall shear stresses (WSS) and velocities were calculated as well as cross-sectional areas (CSA). Furthermore, individual WSS and static pressure distributions were mapped onto the average geometry. The average geometry featured an overall more regular shape that resulted in less resistance, reduced wall shear stresses and velocities compared to the median of the 25 geometries. Spatial distributions of WSS and pressure of average geometry agreed well compared to the average distributions of all individual geometries. The minimal CSA of the average geometry was larger than the median of all individual geometries (83.4 vs. 74.7 mm²). The airflow observed within the average geometry of the healthy nasal cavity did not equal the average airflow of the individual geometries. While differences observed for integral measures were notable, the calculated values for the average geometry lay within the distributions of the individual parameters. Spatially resolved parameters differed less prominently.}, language = {en} } @article{LiPimentelSzengeletal., author = {Li, Jianning and Pimentel, Pedro and Szengel, Angelika and Ehlke, Moritz and Lamecker, Hans and Zachow, Stefan and Estacio, Laura and Doenitz, Christian and Ramm, Heiko and Shi, Haochen and Chen, Xiaojun and Matzkin, Franco and Newcombe, Virginia and Ferrante, Enzo and Jin, Yuan and Ellis, David G. and Aizenberg, Michele R. and Kodym, Oldrich and Spanel, Michal and Herout, Adam and Mainprize, James G. and Fishman, Zachary and Hardisty, Michael R. and Bayat, Amirhossein and Shit, Suprosanna and Wang, Bomin and Liu, Zhi and Eder, Matthias and Pepe, Antonio and Gsaxner, Christina and Alves, Victor and Zefferer, Ulrike and von Campe, Cord and Pistracher, Karin and Sch{\"a}fer, Ute and Schmalstieg, Dieter and Menze, Bjoern H. and Glocker, Ben and Egger, Jan}, title = {AutoImplant 2020 - First MICCAI Challenge on Automatic Cranial Implant Design}, series = {IEEE Transactions on Medical Imaging}, volume = {40}, journal = {IEEE Transactions on Medical Imaging}, number = {9}, issn = {0278-0062}, doi = {10.1109/TMI.2021.3077047}, pages = {2329 -- 2342}, abstract = {The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully automated solutions for cranial implant design. Based on feedback from collaborating neurosurgeons, this paper concludes by stating open issues and post-challenge requirements for intra-operative use.}, language = {en} } @misc{EhlkeRammLameckeretal., author = {Ehlke, Moritz and Ramm, Heiko and Lamecker, Hans and Hege, Hans-Christian and Zachow, Stefan}, title = {Fast Generation of Virtual X-ray Images from Deformable Tetrahedral Meshes}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-41896}, abstract = {We propose a novel GPU-based approach to render virtual X-ray projections of deformable tetrahedral meshes. These meshes represent the shape and the internal density distribution of a particular anatomical structure and are derived from statistical shape and intensity models (SSIMs). We apply our method to improve the geometric reconstruction of 3D anatomy (e.g.\ pelvic bone) from 2D X-ray images. For that purpose, shape and density of a tetrahedral mesh are varied and virtual X-ray projections are generated within an optimization process until the similarity between the computed virtual X-ray and the respective anatomy depicted in a given clinical X-ray is maximized. The OpenGL implementation presented in this work deforms and projects tetrahedral meshes of high resolution (200.000+ tetrahedra) at interactive rates. It generates virtual X-rays that accurately depict the density distribution of an anatomy of interest. Compared to existing methods that accumulate X-ray attenuation in deformable meshes, our novel approach significantly boosts the deformation/projection performance. The proposed projection algorithm scales better with respect to mesh resolution and complexity of the density distribution, and the combined deformation and projection on the GPU scales better with respect to the number of deformation parameters. The gain in performance allows for a larger number of cycles in the optimization process. Consequently, it reduces the risk of being stuck in a local optimum. We believe that our approach contributes in orthopedic surgery, where 3D anatomy information needs to be extracted from 2D X-rays to support surgeons in better planning joint replacements.}, language = {en} } @misc{EhlkeFrenzelRammetal., author = {Ehlke, Moritz and Frenzel, Thomas and Ramm, Heiko and Lamecker, Hans and Akbari Shandiz, Mohsen and Anglin, Carolyn and Zachow, Stefan}, title = {Robust Measurement of Natural Acetabular Orientation from AP Radiographs using Articulated 3D Shape and Intensity Models}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-49824}, language = {en} } @misc{RammMorilloVictoriaTodtetal., author = {Ramm, Heiko and Morillo Victoria, Oscar Salvador and Todt, Ingo and Schirmacher, Hartmut and Ernst, Arneborg and Zachow, Stefan and Lamecker, Hans}, title = {Visual Support for Positioning Hearing Implants}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42495}, abstract = {We present a software planning tool that provides intuitive visual feedback for finding suitable positions of hearing implants in the human temporal bone. After an automatic reconstruction of the temporal bone anatomy the tool pre-positions the implant and allows the user to adjust its position interactively with simple 2D dragging and rotation operations on the bone's surface. During this procedure, visual elements like warning labels on the implant or color encoded bone density information on the bone geometry provide guidance for the determination of a suitable fit.}, language = {en} } @misc{ZilskeLameckerZachow, author = {Zilske, Michael and Lamecker, Hans and Zachow, Stefan}, title = {Adaptive Remeshing of Non-Manifold Surfaces}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-9445}, number = {07-01}, abstract = {We present a unified approach for consistent remeshing of arbitrary non-manifold triangle meshes with additional user-defined feature lines, which together form a feature skeleton. Our method is based on local operations only and produces meshes of high regularity and triangle quality while preserving the geometry as well as topology of the feature skeleton and the input mesh.}, language = {en} } @misc{LameckerLangeSeebass, author = {Lamecker, Hans and Lange, Thomas and Seebass, Martin}, title = {Segmentation of the Liver using a 3D Statistical Shape Model}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-7847}, number = {04-09}, abstract = {This paper presents an automatic approach for segmentation of the liver from computer tomography (CT) images based on a 3D statistical shape model. Segmentation of the liver is an important prerequisite in liver surgery planning. One of the major challenges in building a 3D shape model from a training set of segmented instances of an object is the determination of the correspondence between different surfaces. We propose to use a geometric approach that is based on minimizing the distortion of the correspondence mapping between two different surfaces. For the adaption of the shape model to the image data a profile model based on the grey value appearance of the liver and its surrounding tissues in contrast enhanced CT data was developed. The robustness of this method results from a previous nonlinear diffusion filtering of the image data. Special focus is turned to the quantitative evaluation of the segmentation process. Several different error measures are discussed and implemented in a study involving more than 30 livers.}, language = {en} } @phdthesis{Lamecker, author = {Lamecker, Hans}, title = {Variational and statistical shape modeling for 3D geometry reconstruction}, abstract = {The reconstruction of geometric shapes plays an important role in many biomedical applications. One example is the patient-specific, computer-aided planning of complex interventions, which requires the generation of explicitly represented geometric models of anatomical structures from medical image data. Only solutions that require minimal interaction by medical personnel are likely to enter clinical routine. Another example is the planning of surgical corrections of deformities where the target shape is unknown. Surgeons are often forced to resort to subjective criteria. These applications still pose highly challenging reconstruction problems, which are addressed in this thesis. The fundamental hypothesis, pursued in this thesis, is that the problems can be solved by incorporating a-priori knowledge about shape and other application-specific characteristics. Here, we focus mainly on the aspect of geometric shape analysis. The basic idea is to capture the most essential variations of a certain class of geometric objects via statistical shape models, which model typical features contained in a given population, and restrict the outcome of a reconstruction algorithm (more or less) to the space spanned by such models. A fundamental prerequisite for performing statistical shape analysis on a set of different objects is the identification of corresponding points on their associated surfaces. This problem is particularly difficult to solve if the shapes stem from different individuals. The reason lies in the basic difficulty of defining suitable measures of similarity. In this thesis, we divide the correspondence problem into feature and non-feature matching. The feature part depends on the application, while the non-feature part can be characterized by a purely geometric description. We propose two different approaches. The first approach has proved useful in many applications. Yet, it suffers from some practical limitations and does not yield a measure of similarity. Our second, variational, approach is designed to overcome these limitations. In it, we propose to minimize an invariant stretching measure, constrained by previously computed features. An important property, which sets our method apart from previous work, is that it does not require the computation of a global surface parameterization.}, language = {en} } @misc{EhlkeRammLameckeretal., author = {Ehlke, Moritz and Ramm, Heiko and Lamecker, Hans and Zachow, Stefan}, title = {Efficient projection and deformation of volumetric intensity models for accurate simulation of X-ray images}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-16580}, abstract = {We present an efficient GPU-based method to generate virtual X-ray images from tetrahedral meshes which are associated with attenuation values. In addition, a novel approach is proposed that performs the model deformation on the GPU. The tetrahedral grids are derived from volumetric statistical shape and intensity models (SSIMs) and describe anatomical structures. Our research targets at reconstructing 3D anatomical shapes by comparing virtual X-ray images generated using our novel approach with clinical data while varying the shape and density of the SSIM in an optimization process. We assume that a deformed SSIM adequately represents an anatomy of interest when the similarity between the virtual and the clinical X-ray image is maximized. The OpenGL implementation presented here generates accurate (virtual) X-ray images at interactive rates, thus qualifying it for its use in the reconstruction process.}, language = {en} } @article{SekuboyinaHusseiniBayatetal., author = {Sekuboyina, Anjany and Husseini, Malek E. and Bayat, Amirhossein and L{\"o}ffler, Maximilian and Liebl, Hans and Li, Hongwei and Tetteh, Giles and Kukačka, Jan and Payer, Christian and Štern, Darko and Urschler, Martin and Chen, Maodong and Cheng, Dalong and Lessmann, Nikolas and Hu, Yujin and Wang, Tianfu and Yang, Dong and Xu, Daguang and Ambellan, Felix and Amiranashvili, Tamaz and Ehlke, Moritz and Lamecker, Hans and Lehnert, Sebastian and Lirio, Marilia and de Olaguer, Nicol{\´a}s P{\´e}rez and Ramm, Heiko and Sahu, Manish and Tack, Alexander and Zachow, Stefan and Jiang, Tao and Ma, Xinjun and Angerman, Christoph and Wang, Xin and Brown, Kevin and Kirszenberg, Alexandre and Puybareau, {\´E}lodie and Chen, Di and Bai, Yiwei and Rapazzo, Brandon H. and Yeah, Timyoas and Zhang, Amber and Xu, Shangliang and Hou, Feng and He, Zhiqiang and Zeng, Chan and Xiangshang, Zheng and Liming, Xu and Netherton, Tucker J. and Mumme, Raymond P. and Court, Laurence E. and Huang, Zixun and He, Chenhang and Wang, Li-Wen and Ling, Sai Ho and Huynh, L{\^e} Duy and Boutry, Nicolas and Jakubicek, Roman and Chmelik, Jiri and Mulay, Supriti and Sivaprakasam, Mohanasankar and Paetzold, Johannes C. and Shit, Suprosanna and Ezhov, Ivan and Wiestler, Benedikt and Glocker, Ben and Valentinitsch, Alexander and Rempfler, Markus and Menze, Bj{\"o}rn H. and Kirschke, Jan S.}, title = {VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images}, series = {Medical Image Analysis}, volume = {73}, journal = {Medical Image Analysis}, doi = {10.1016/j.media.2021.102166}, abstract = {Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.}, language = {en} } @article{SekuboyinaBayatHusseinietal., author = {Sekuboyina, Anjany and Bayat, Amirhossein and Husseini, Malek E. and L{\"o}ffler, Maximilian and Li, Hongwei and Tetteh, Giles and Kukačka, Jan and Payer, Christian and Štern, Darko and Urschler, Martin and Chen, Maodong and Cheng, Dalong and Lessmann, Nikolas and Hu, Yujin and Wang, Tianfu and Yang, Dong and Xu, Daguang and Ambellan, Felix and Amiranashvili, Tamaz and Ehlke, Moritz and Lamecker, Hans and Lehnert, Sebastian and Lirio, Marilia and de Olaguer, Nicol{\´a}s P{\´e}rez and Ramm, Heiko and Sahu, Manish and Tack, Alexander and Zachow, Stefan and Jiang, Tao and Ma, Xinjun and Angerman, Christoph and Wang, Xin and Wei, Qingyue and Brown, Kevin and Wolf, Matthias and Kirszenberg, Alexandre and Puybareau, {\´E}lodie and Valentinitsch, Alexander and Rempfler, Markus and Menze, Bj{\"o}rn H. and Kirschke, Jan S.}, title = {VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images}, series = {arXiv}, journal = {arXiv}, language = {en} } @article{WilsonAnglinAmbellanetal., author = {Wilson, David and Anglin, Carolyn and Ambellan, Felix and Grewe, Carl Martin and Tack, Alexander and Lamecker, Hans and Dunbar, Michael and Zachow, Stefan}, title = {Validation of three-dimensional models of the distal femur created from surgical navigation point cloud data for intraoperative and postoperative analysis of total knee arthroplasty}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {12}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {12}, publisher = {Springer}, doi = {10.1007/s11548-017-1630-5}, pages = {2097 -- 2105}, abstract = {Purpose: Despite the success of total knee arthroplasty there continues to be a significant proportion of patients who are dissatisfied. One explanation may be a shape mismatch between pre and post-operative distal femurs. The purpose of this study was to investigate a method to match a statistical shape model (SSM) to intra-operatively acquired point cloud data from a surgical navigation system, and to validate it against the pre-operative magnetic resonance imaging (MRI) data from the same patients. Methods: A total of 10 patients who underwent navigated total knee arthroplasty also had an MRI scan less than 2 months pre-operatively. The standard surgical protocol was followed which included partial digitization of the distal femur. Two different methods were employed to fit the SSM to the digitized point cloud data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). The available MRI data were manually segmented and the reconstructed three-dimensional surfaces used as ground truth against which the statistical shape model fit was compared. Results: For both approaches, the difference between the statistical shape model-generated femur and the surface generated from MRI segmentation averaged less than 1.7 mm, with maximum errors occurring in less clinically important areas. Conclusion: The results demonstrated good correspondence with the distal femoral morphology even in cases of sparse data sets. Application of this technique will allow for measurement of mismatch between pre and post-operative femurs retrospectively on any case done using the surgical navigation system and could be integrated into the surgical navigation unit to provide real-time feedback.}, language = {en} } @misc{GreweLameckerZachow2013, author = {Grewe, Carl Martin and Lamecker, Hans and Zachow, Stefan}, title = {Landmark-based Statistical Shape Analysis}, series = {Auxology - Studying Human Growth and Development url}, journal = {Auxology - Studying Human Growth and Development url}, editor = {Hermanussen, Michael}, publisher = {Schweizerbart Verlag, Stuttgart}, pages = {199 -- 201}, year = {2013}, language = {en} } @misc{GreweLameckerZachow2011, author = {Grewe, Carl Martin and Lamecker, Hans and Zachow, Stefan}, title = {Digital morphometry: The Potential of Statistical Shape Models}, series = {Anthropologischer Anzeiger. Journal of Biological and Clinical Anthropology}, journal = {Anthropologischer Anzeiger. Journal of Biological and Clinical Anthropology}, pages = {506 -- 506}, year = {2011}, language = {en} }