@article{AkbariShandizBoulosSavarssonetal.2018, author = {Akbari Shandiz, Mohsen and Boulos, Paul and S{\ae}varsson, Stefan and Ramm, Heiko and Fu, Chun Kit and Miller, Stephen and Zachow, Stefan and Anglin, Carolyn}, title = {Changes in Knee Shape and Geometry Resulting from Total Knee Arthroplasty}, volume = {232}, journal = {Journal of Engineering in Medicine}, number = {1}, doi = {10.1177/0954411917743274}, pages = {67 -- 79}, year = {2018}, abstract = {Changes in knee shape and geometry resulting from total knee arthroplasty can affect patients in numerous important ways: pain, function, stability, range of motion, and kinematics. Quantitative data concerning these changes have not been previously available, to our knowledge, yet are essential to understand individual experiences of total knee arthroplasty and thereby improve outcomes for all patients. The limiting factor has been the challenge of accurately measuring these changes. Our study objective was to develop a conceptual framework and analysis method to investigate changes in knee shape and geometry, and prospectively apply it to a sample total knee arthroplasty population. Using clinically available computed tomography and radiography imaging systems, the three-dimensional knee shape and geometry of nine patients (eight varus and one valgus) were compared before and after total knee arthroplasty. All patients had largely good outcomes after their total knee arthroplasty. Knee shape changed both visually and numerically. On average, the distal condyles were slightly higher medially and lower laterally (range: +4.5 mm to -4.4 mm), the posterior condyles extended farther out medially but not laterally (range: +1.8 to -6.4 mm), patellofemoral distance increased throughout flexion by 1.8-3.5 mm, and patellar thickness alone increased by 2.9 mm (range: 0.7-5.2 mm). External femoral rotation differed preop and postop. Joint line distance, taking cartilage into account, changed by +0.7 to -1.5 mm on average throughout flexion. Important differences in shape and geometry were seen between pre-total knee arthroplasty and post-total knee arthroplasty knees. While this is qualitatively known, this is the first study to report it quantitatively, an important precursor to identifying the reasons for the poor outcome of some patients. Using the developed protocol and visualization techniques to compare patients with good versus poor clinical outcomes could lead to changes in implant design, implant selection, component positioning, and surgical technique. Recommendations based on this sample population are provided. Intraoperative and postoperative feedback could ultimately improve patient satisfaction.}, language = {en} } @article{SaevarssonSharmaAmirietal.2012, author = {Saevarsson, Stefan and Sharma, Gulshan and Amiri, Shahram and Montgomery, Sigrun and Ramm, Heiko and Lichti, Derek and Lieck, Robert and Zachow, Stefan and Anglin, Carolyn}, title = {Radiological method for measuring patellofemoral tracking and tibiofemoral kinematics before and after total knee replacement}, volume = {1}, journal = {Bone and Joint Research}, number = {10}, doi = {10.1302/2046-3758.110.2000117}, pages = {263 -- 271}, year = {2012}, language = {en} } @article{HildebrandtGoubergritsHepptetal.2013, author = {Hildebrandt, Thomas and Goubergrits, Leonid and Heppt, Werner and Bessler, Stefan and Zachow, Stefan}, title = {Evaluation of the Intranasal Flow Field through Computational Fluid Dynamics (CFD)}, volume = {29}, journal = {Journal of Facial and Plastic Surgery}, number = {2}, publisher = {Thieme}, doi = {10.1055/s-0033-1341591}, pages = {93 -- 98}, year = {2013}, language = {en} } @article{SaevarssonSharmaRammetal.2013, author = {Saevarsson, Stefan and Sharma, Gulshan and Ramm, Heiko and Lieck, Robert and Hutchison, Carol and Werle, Jason and Montgomery, Sigrun and Romeo, Carolina and Zachow, Stefan and Anglin, Carolyn}, title = {Kinematic Differences Between Gender Specific And Traditional Knee Implants}, volume = {28}, journal = {The Journal of Arthroplasty}, number = {9}, doi = {10.1016/j.arth.2013.01.021}, pages = {1543 -- 1550}, year = {2013}, language = {en} } @misc{SharmaHoSaevarssonetal.2012, author = {Sharma, Gulshan and Ho, Karen and Saevarsson, Stefan and Ramm, Heiko and Lieck, Robert and Zachow, Stefan and Anglin, Carolyn}, title = {Knee Pose and Geometry Pre- and Post-Total Knee Arthroplasty Using Computed Tomography}, journal = {58th Annual Meeting of the Orthopaedic Research Society (ORS)}, address = {San Francisco, CA}, year = {2012}, language = {en} } @misc{SharmaSaevarssonAmirietal.2012, author = {Sharma, Gulshan and Saevarsson, Stefan and Amiri, Shahram and Montgomery, Sigrun and Ramm, Heiko and Lichti, Derek and Zachow, Stefan and Anglin, Carolyn}, title = {Sequential-Biplane Radiography for Measuring Pre and Post Total Knee Arthroplasty Kinematics}, journal = {58th Annual Meeting of the Orthopaedic Research Society (ORS)}, address = {San Francisco, CA}, year = {2012}, language = {en} } @inproceedings{StefanGulshanSigrunetal.2012, author = {Stefan, Saevarsson and Gulshan, Sharma and Sigrun, Montgomery and Karen, Ho and Ramm, Heiko and Lieck, Robert and Zachow, Stefan and Hutchison, Carol and Jason, Werle and Carolyn, Anglin}, title = {Kinematic Comparison Between Gender Specific and Traditional Femoral Implants}, booktitle = {67th Canadian Orthopaedic Association (COA) Annual Meeting}, year = {2012}, language = {en} } @article{HoSaevarssonRammetal.2012, author = {Ho, Karen and Saevarsson, Stefan and Ramm, Heiko and Lieck, Robert and Zachow, Stefan and Sharma, Gulshan and Rex, Erica and Amiri, Shahram and Wu, Barnabas and Leumann, Andre and Anglin, Carolyn}, title = {Computed tomography analysis of knee pose and geometry before and after total knee arthroplasty}, volume = {45}, journal = {Journal of biomechanics}, number = {13}, doi = {10.1016/j.jbiomech.2012.06.004}, pages = {2215 -- 21}, year = {2012}, language = {en} } @article{XieGruberCrampenetal.2025, author = {Xie, Kunpeng and Gruber, Lennart Johannes and Crampen, Martin and Li, Yao and Ferreira, Andr{\´e} and Tappeiner, Elias and Gillot, Maxime and Schepers, Jan and Xu, Jiangchang and Pankert, Tobias and Beyer, Michel and Shahamiri, Negar and ten Brink, Reinier and Dot, Gauthier and Weschke, Charlotte and van Nistelrooij, Niels and Verhelst, Pieter-Jan and Guo, Yan and Xu, Zhibin and Bienzeisler, Jonas and Rashad, Ashkan and Fl{\"u}gge, Tabea and Cotton, Ross and Vinayahalingam, Shankeeth and Ilesan, Robert and Raith, Stefan and Madsen, Dennis and Seibold, Constantin and Xi, Tong and Berg{\´e}, Stefaan and Nebelung, Sven and Kodym, Oldřich and Sundqvist, Osku and Thieringer, Florian and Lamecker, Hans and Coppens, Antoine and Potrusil, Thomas and Kraeima, Joep and Witjes, Max and Wu, Guomin and Chen, Xiaojun and Lambrechts, Adriaan and Cevidanes, Lucia H Soares and Zachow, Stefan and Hermans, Alexander and Truhn, Daniel and Alves, Victor and Egger, Jan and R{\"o}hrig, Rainer and H{\"o}lzle, Frank and Puladi, Behrus}, title = {Beyond Benchmarks: Towards Robust Artificial Intelligence Bone Segmentation in Socio-Technical Systems}, volume = {299}, journal = {Expert Systems With Applications}, number = {Part D}, doi = {10.1016/j.eswa.2025.130031}, year = {2025}, abstract = {Despite the advances in automated medical image segmentation, AI models still underperform in various clinical settings, challenging real-world integration. In this multicenter evaluation, we analyzed 20 state-of-the-art mandibular segmentation models across 19,218 segmentations of 1,000 clinically resampled CT/CBCT scans. We show that segmentation accuracy varies by up to 25\% depending on socio-technical factors such as voxel size, bone orientation, and patient conditions such as osteosynthesis or pathology. Higher sharpness, isotropic smaller voxels, and neutral orientation significantly improved results, while metallic osteosynthesis and anatomical complexity led to significant degradation. Our findings challenge the common view of AI models as "plug-and-play" tools and suggest evidence-based optimization recommendations for both clinicians and developers. This will in turn boost the integration of AI segmentation tools in routine healthcare.}, language = {en} } @misc{DeuflhardDoesselLouisetal.2008, author = {Deuflhard, Peter and D{\"o}ssel, Olaf and Louis, Alfred and Zachow, Stefan}, title = {Mehr Mathematik wagen in der Medizin}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10776}, number = {08-25}, year = {2008}, abstract = {Der Artikel gibt einen Einblick in das reiche Feld der Zusammenarbeit zwischen Mathematik und Medizin. Beispielhaft werden drei Erfolgsmodelle dargestellt: Medizinische Bildgebung, mathematische Modellierung und Biosignalverarbeitung im Bereich der Dynamik des Herzens sowie mathematische Modellierung und Simulation in der Krebstherapie Hyperthermie und der Mund-Kiefer-Gesichts-Chirurgie. In allen F{\"a}llen existiert ein Gleichklang der Interessen von Medizin und Mathematik: Beide Disziplinen wollen die Resultate schnell und zuverl{\"a}ssig. F{\"u}r die Klinik heißt das, dass notwendige Rechnungen in m{\"o}glichst kurzer Zeit, und zwar auf dem PC, ablaufen m{\"u}ssen und dass die Resultate so genau und belastbar sein m{\"u}ssen, dass medizinische Entscheidungen darauf aufbauen k{\"o}nnen. F{\"u}r die Mathematik folgt daraus, dass h{\"o}chste Anforderungen an die Effizienz der verwendeten Algorithmen und die darauf aufbauende Software in Numerik und Visualisierung zu stellen sind. Jedes Kapitel endet mit einer Darstellung der Perspektive des jeweiligen Gebietes. Abschließend werden m{\"o}gliche Handlungsoptionen f{\"u}r Politik und Wirtschaft diskutiert.}, language = {de} } @misc{ZilskeLameckerZachow2007, 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}, year = {2007}, 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{Zachow1999, type = {Master Thesis}, author = {Zachow, Stefan}, title = {Design and Implementation of a planning system for episthetic surgery}, year = {1999}, language = {en} } @misc{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 from Deformable Tetrahedral Meshes}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-41896}, year = {2013}, 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} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Validation of a Linear Elastic Model for Soft Tissue Simulation in Craniofacial Surgery}, volume = {4319}, booktitle = {Proc. SPIE Medical Imaging 2001}, editor = {Mun, Seong}, address = {San Diego, USA}, doi = {10.1117/12.428061}, pages = {27 -- 35}, year = {2001}, language = {en} } @inproceedings{GladilinZachowHegeetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Hege, Hans-Christian and Deuflhard, Peter}, title = {FE-based heuristic approach for the estimation of person-specific facial mimics}, booktitle = {Proceedings of Euro-Par 2001: 5-th International Symposium on Computer Methods}, address = {Rome, Italy}, year = {2001}, language = {en} } @inproceedings{GladilinZachowHegeetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Hege, Hans-Christian and Deuflhard, Peter}, title = {Towards a Realistic Simulation of Individual Facial Mimics}, booktitle = {Vision Modeling and Visualization 2001 (VMV)}, address = {Stuttgart, Germany}, pages = {129 -- 134}, year = {2001}, language = {en} } @inproceedings{ZachowGladilinZeilhoferetal.2001, author = {Zachow, Stefan and Gladilin, Evgeny and Zeilhofer, Hans-Florian and Sader, Robert}, title = {Improved 3D Osteotomy Planning in Cranio-Maxillofacial Surgery}, booktitle = {Proc. Medical Image Computing and Computer-Assisted Intervention (MICCAI 2001)}, address = {Utrecht, The Netherlands}, doi = {10.1007/3-540-45468-3_57}, pages = {473 -- 481}, year = {2001}, language = {en} } @inproceedings{ZachowGladilinZeilhoferetal.2001, author = {Zachow, Stefan and Gladilin, Evgeny and Zeilhofer, Hans-Florian and Sader, Robert}, title = {3D Osteotomieplanung in der MKG-Chirurgie unter Ber{\"u}cksichtigung der r{\"a}umlichen Weichgewebeanordnung}, booktitle = {Rechner- und sensorgest{\"u}tzte Chirurgie, GI Proc. zur SFB 414 Tagung}, address = {Heidelberg}, pages = {217 -- 226}, year = {2001}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {A Biomechanical Model for Soft Tissue Simulation in Craniofacial Surgery}, booktitle = {Medical Imaging and Augmented Reality (MIAR)}, address = {Hong Kong, China}, doi = {10.1109/MIAR.2001.930276}, pages = {137 -- 141}, year = {2001}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Virtual Fibers: A Robust Approach for Muscle Simulation}, booktitle = {IX Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)}, address = {Pula, Croatia}, pages = {961 -- 964}, year = {2001}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Validierung eines linear elastischen Modells f{\"u}r die Weichgewebesimulation in der Mund-Kiefer-Gesichtschirurgie}, booktitle = {Bildverarbeitung f{\"u}r die Medizin (BVM)}, address = {L{\"u}beck, Germany}, pages = {57 -- 61}, year = {2001}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2003, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Realistic prediction of individual facial emotion expressions for craniofacial surgery simulations}, volume = {5029}, booktitle = {Proc. SPIE medical Imaging 2003}, editor = {Galloway, Robert}, address = {San Diego, CA, USA}, doi = {10.1117/12.479584}, pages = {520 -- 527}, year = {2003}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2003, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {On constitutive modeling of soft tissue for the long-term prediction of cranio-maxillofacial surgery outcome}, volume = {1256}, booktitle = {International Congress Series, CARS2003, Computer Assisted Radiology and Surgery, Proceedings of the 17th International Congress and Exhibition}, doi = {10.1016/S0531-5131(03)00500-4}, pages = {343 -- 348}, year = {2003}, language = {en} } @inproceedings{ZachowGladilinSaderetal.2003, author = {Zachow, Stefan and Gladilin, Evgeny and Sader, Robert and Zeilhofer, Hans-Florian}, title = {Draw \& Cut: Intuitive 3D Osteotomy Planning on Polygonal Bone Models}, booktitle = {Computer Assisted Radiology and Surgery (CARS)}, address = {London, UK}, doi = {10.1016/S0531-5131(03)00272-3}, pages = {362 -- 369}, year = {2003}, language = {en} } @article{GladilinZachowDeuflhardetal.2004, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Anatomy- and physics-based facial animation for craniofacial surgery simulations}, volume = {42(2)}, journal = {Med Biol Eng Comput.}, doi = {10.1007/BF02344627}, pages = {167 -- 170}, year = {2004}, language = {en} } @inproceedings{ZachowGladilinHegeetal.2002, author = {Zachow, Stefan and Gladilin, Evgeny and Hege, Hans-Christian and Deuflhard, Peter}, title = {Towards Patient Specific, Anatomy Based Simulation of Facial Mimics for Surgical Nerve Rehabilitation}, booktitle = {Computer Assisted Radiology and Surgery (CARS)}, publisher = {Springer Verlag}, pages = {3 -- 6}, year = {2002}, language = {en} } @article{ZachowGladilinTrepczynskietal.2002, author = {Zachow, Stefan and Gladilin, Evgeny and Trepczynski, Adam and Sader, Robert and Zeilhofer, Hans-Florian}, title = {3D Osteotomy Planning in Cranio-Maxillofacial Surgery: Experiences and Results of Surgery Planning and Volumetric Finite-Element Soft Tissue Prediction in Three Clinical Cases}, journal = {Computer Assisted Radiology and Surgery (CARS)}, publisher = {Springer Verlag}, pages = {983 -- 987}, year = {2002}, language = {en} } @inproceedings{ZachowErdmannHegeetal.2004, author = {Zachow, Stefan and Erdmann, Bodo and Hege, Hans-Christian and Deuflhard, Peter}, title = {Advances in 3D osteotomy planning with 3D soft tissue prediction}, booktitle = {Proc. 2nd International Symposium on Computer Aided Surgery around the Head, Abstract}, address = {Bern}, pages = {31}, year = {2004}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2002, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Adaptive Nonlinear Elastic FEM for Realistic Prediction of Soft Tissue in Craniofacial Surgery Simulations}, volume = {4681}, booktitle = {Proc. SPIE Medical Imaging 2002}, editor = {K. Mun, Seong}, address = {San Diego, USA}, doi = {10.1117/12.466906}, pages = {1 -- 8}, year = {2002}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2002, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Shape-based Modeling Approach for the Estimation of Individual Facial Mimics in Craniofacial Surgery Planning}, volume = {4681}, booktitle = {Proc. SPIE Medical Imaging 2002: Visualization, Image-Guided Procedures, and Display}, editor = {Mun, Seong}, address = {San Diego, USA target}, pages = {242 -- 248}, year = {2002}, 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}, booktitle = {Proceedings of the Japan Korea Computer Graphics Conference 2002}, publisher = {Kanazawa University}, address = {Kanazawa City, Ishikawa, Japan}, year = {2002}, 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}, 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}, 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{ZachowHegeDeuflhard2006, author = {Zachow, Stefan and Hege, Hans-Christian and Deuflhard, Peter}, title = {Computer assisted planning in cranio-maxillofacial surgery}, volume = {14(1)}, journal = {Journal of Computing and Information Technology}, pages = {53 -- 64}, 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?}, journal = {Int. J. of Computer Assisted Radiology and Surgery}, publisher = {Springer}, pages = {415 -- 417}, year = {2006}, language = {en} } @article{ZachowSteinmannHildebrandtetal.2006, author = {Zachow, Stefan and Steinmann, Alexander and Hildebrandt, Thomas and Weber, Rainer and Heppt, Werner}, title = {CFD simulation of nasal airflow: Towards treatment planning for functional rhinosurgery}, journal = {Int. J. of Computer Assisted Radiology and Surgery}, publisher = {Springer}, pages = {165 -- 167}, year = {2006}, language = {en} } @inproceedings{HierlWollnyZachowetal.2002, author = {Hierl, Thomas and Wollny, Gert and Zachow, Stefan and Kl{\"o}ppel, Rainer}, title = {Visualisierung von Knochen und Weichteilver{\"a}nderungen in der Distraktionsosteogenese des Mittelgesichtes}, booktitle = {Proc. 10. Jahrestagung der Deutschen Gesellschaft f{\"u}r Sch{\"a}delbasischirurgie}, address = {Heidelberg}, pages = {111 -- 116}, year = {2002}, language = {en} } @inproceedings{ZachowGladilinHegeetal.2000, author = {Zachow, Stefan and Gladilin, Evgeny and Hege, Hans-Christian and Deuflhard, Peter}, title = {Finite-Element Simulation of Soft Tissue Deformation}, booktitle = {Computer Assisted Radiology and Surgey (CARS)}, publisher = {Elsevier Science B.V.}, pages = {23 -- 28}, year = {2000}, language = {en} } @inproceedings{ZachowLuethStallingetal.1999, author = {Zachow, Stefan and Lueth, Tim and Stalling, Detlev and Hein, Andreas and Klein, Martin and Menneking, Horst}, title = {Optimized Arrangement of Osseointegrated Implants: A Surgical Planning System for the Fixation of Facial Protheses}, booktitle = {Computer Assisted Radiology and Surgery (CARS'99)}, publisher = {Elsevier Science B.V.}, pages = {942 -- 946}, year = {1999}, language = {en} } @inproceedings{HeinLuethZachowetal.1999, author = {Hein, Andreas and Lueth, Tim and Zachow, Stefan and Stien, Malte}, title = {A 2D Planning Sytem for Robot-Assisted Interventions}, booktitle = {Computer Assisted Radiology and Surgery}, publisher = {Elsevier Science B.V.}, pages = {1049}, year = {1999}, language = {en} } @inproceedings{StallingSeebassZachow1999, author = {Stalling, Detlev and Seebaß, Martin and Zachow, Stefan}, title = {Mehrschichtige Oberfl{\"a}chenmodelle zur computergest{\"u}tzten Planung in der Chirurgie}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 1999 - Algorithmen, Anwendungen}, publisher = {Springer-Verlag, Berlin}, pages = {203 -- 207}, year = {1999}, language = {en} } @phdthesis{Zachow2005, author = {Zachow, Stefan}, title = {Computer assisted osteotomy planning in cranio-maxillofacial surgery under consideration of facial soft tissue changes}, year = {2005}, language = {en} } @misc{EhlkeRammLameckeretal.2012, 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}, year = {2012}, 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} } @misc{RammMorilloVictoriaTodtetal.2013, 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}, year = {2013}, 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{AmbellanLameckervonTycowiczetal.2019, 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}, year = {2019}, 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} } @misc{AmbellanTackEhlkeetal.2019, author = {Ambellan, Felix and Tack, Alexander and Ehlke, Moritz and Zachow, Stefan}, title = {Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-72704}, year = {2019}, abstract = {We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging (MRI) that combines a priori knowledge of anatomical shape with Convolutional Neural Networks (CNNs).The proposed approach incorporates 3D Statistical Shape Models (SSMs) as well as 2D and 3D CNNs to achieve a robust and accurate segmentation of even highly pathological knee structures.The shape models and neural networks employed are trained using data from the Osteoarthritis Initiative (OAI) and the MICCAI grand challenge "Segmentation of Knee Images 2010" (SKI10), respectively. We evaluate our method on 40 validation and 50 submission datasets from the SKI10 challenge.For the first time, an accuracy equivalent to the inter-observer variability of human readers is achieved in this challenge.Moreover, the quality of the proposed method is thoroughly assessed using various measures for data from the OAI, i.e. 507 manual segmentations of bone and cartilage, and 88 additional manual segmentations of cartilage. Our method yields sub-voxel accuracy for both OAI datasets. We make the 507 manual segmentations as well as our experimental setup publicly available to further aid research in the field of medical image segmentation.In conclusion, combining localized classification via CNNs with statistical anatomical knowledge via SSMs results in a state-of-the-art segmentation method for knee bones and cartilage from MRI data.}, language = {en} } @incollection{AmbellanLameckervonTycowiczetal.2019, author = {Ambellan, Felix and Lamecker, Hans and von Tycowicz, Christoph and Zachow, Stefan}, title = {Statistical Shape Models - Understanding and Mastering Variation in Anatomy}, 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}, year = {2019}, 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.2019, 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}, volume = {35}, journal = {Facial Plastic Surgery}, number = {1}, doi = {10.1055/s-0039-1677721}, pages = {9 -- 13}, year = {2019}, 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.2019, 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}, volume = {35}, journal = {Facial Plastic Surgery}, number = {1}, doi = {10.1055/s-0039-1677720}, pages = {1 -- 8}, year = {2019}, 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} } @inproceedings{TackZachow2019, author = {Tack, Alexander and Zachow, Stefan}, title = {Accurate Automated Volumetry of Cartilage of the Knee using Convolutional Neural Networks: Data from the Osteoarthritis Initiative}, booktitle = {IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)}, doi = {10.1109/ISBI.2019.8759201}, pages = {40 -- 43}, year = {2019}, abstract = {Volumetry of cartilage of the knee is needed for knee osteoarthritis (KOA) assessment. It is typically performed manually in a tedious and subjective process. We developed a method for an automated, segmentation-based quantification of cartilage volume by employing 3D Convolutional Neural Networks (CNNs). CNNs were trained in a supervised manner using magnetic resonance imaging data and cartilage volumetry readings performed by clinical experts for 1378 subjects provided by the Osteoarthritis Initiative. It was shown that 3D CNNs are able to achieve volume measures comparable to the magnitude of variation between expert readings and the real in vivo situation. In the future, accurate automated cartilage volumetry might support both, diagnosis of KOA as well as longitudinal analysis of KOA progression.}, language = {en} }