@article{HierlZachowWollnyetal.2004, author = {Hierl, Thomas and Zachow, Stefan and Wollny, Gert and Berti, Guntram and Schmidt, Jens-Georg and Fingberg, Jochen}, title = {Concepts of computer-based simulation in orthognathic surgery}, series = {Journal of Cranio-Maxillofacial Surgery 32 Suppl. 1}, journal = {Journal of Cranio-Maxillofacial Surgery 32 Suppl. 1}, pages = {81 -- 82}, year = {2004}, 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} } @article{ZachowDeuflhard2008, author = {Zachow, Stefan and Deuflhard, Peter}, title = {Computergest{\"u}tzte Planung in der kraniofazialen Chirurgie}, series = {Face 01/08, Int. Mag. of Orofacial Esthetics}, journal = {Face 01/08, Int. Mag. of Orofacial Esthetics}, publisher = {Oemus Journale Leipzig}, pages = {43 -- 49}, year = {2008}, language = {en} } @incollection{RammZachow2012, author = {Ramm, Heiko and Zachow, Stefan}, title = {Computergest{\"u}tzte Planung f{\"u}r die individuelle Implantatversorgung}, series = {Health Academy}, volume = {16}, booktitle = {Health Academy}, editor = {Niederlag, Wolfgang and Lemke, Heinz and Peitgen, Heinz-Otto and Lehrach, Hans}, pages = {145 -- 158}, year = {2012}, language = {de} } @inproceedings{ZachowHegeDeuflhard2004, author = {Zachow, Stefan and Hege, Hans-Christian and Deuflhard, Peter}, title = {Computergest{\"u}tzte Operationsplanung in der Gesichtschirurgie}, series = {Proc. VDE Kongress 2004 - Innovationen f{\"u}r Menschen, Band 2, Fachtagungsberichte DGBMT - GMM - GMA}, booktitle = {Proc. VDE Kongress 2004 - Innovationen f{\"u}r Menschen, Band 2, Fachtagungsberichte DGBMT - GMM - GMA}, pages = {53 -- 58}, year = {2004}, language = {en} } @phdthesis{Zachow, author = {Zachow, Stefan}, title = {Computergest{\"u}tzte 3D Osteotomieplanung in der Mund-Kiefer-Gesichtschirurgie unter Ber{\"u}cksichtigung der r{\"a}umlichen Weichgewebeanordnung}, isbn = {3899631986}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-10432}, abstract = {In der Arbeit wird die computergest{\"u}tzte Planung von chirurgisch gesetzten Knochenfrakturen bzw. Knochenschnitten (sogenannten Osteotomien) an dreidimensionalen, computergrafischen Sch{\"a}delmodellen, sowie die Umpositionierung separierter kn{\"o}cherner Segmente im Kontext der rekonstruktiven MKG-Chirurgie behandelt. Durch die 3D Modellierung und Visualisierung anatomischer Strukturen, sowie der 3D Osteotomie- und Umstellungsplanung unter Einbeziehung der resultierenden Weichgewebedeformation wird den Chirurgen ein Werkzeug an die Hand gegeben, mit dem eine Therapieplanung am Computer durchgef{\"u}hrt und diese in Hinblick auf Funktion und {\"A}sthetik bewertet werden kann. Unterschiedliche Strategien k{\"o}nnen dabei erprobt und in ihrer Auswirkung erfasst werden. Dazu wird ein methodischer Ansatz vorgestellt, der zum einen die chirurgische Planung im Vergleich zu existierenden Ans{\"a}tzen deutlich verbessert und zum anderen eine robuste Weichgewebeprognose, durch den Einsatz geeigneter Planungsmodelle und eines physikalisch basierten Weichgewebemodells unter Nutzung numerischer L{\"o}sungsverfahren in die Planung integriert. Die Visualisierung der Planungsergebnisse erlaubt sowohl eine anschauliche und {\"u}berzeugende, pr{\"a}operative Patientenaufkl{\"a}rung, als auch die Demonstration m{\"o}glicher Vorgehensweisen und deren Auswirkungen f{\"u}r die chirurgische Ausbildung. Ferner erg{\"a}nzen die Planungsdaten die Falldokumentation und liefern einen Beitrag zur Qualit{\"a}tssicherung. Die Arbeit ist in sieben Kapitel gegliedert und wie folgt strukturiert: Zuerst wird die medizinische Aufgabenstellung bei der chirurgischen Rekonstruktion von Knochenfehlbildungen und -fehlstellungen in der kraniofazialen Chirurgie sowie die daraus resultierenden Anforderungen an die Therapieplanung beschrieben. Anschließend folgt ein umfassender {\"U}berblick {\"u}ber entsprechende Vorarbeiten zur computergest{\"u}tzten Planung knochenverlagernder Operationen und eine kritische Bestandsaufnahme der noch vorhandenen Defizite. Nach der Vorstellung des eigenen Planungsansatzes wird die Generierung individueller, qualitativ hochwertiger 3D Planungsmodelle aus tomografischen Bilddaten beschrieben, die den Anforderungen an eine intuitive, 3D Planung von Umstellungsosteotomien entsprechen und eine Simulation der daraus resultierenden Weichgewebedeformation mittels der Finite-Elemente Methode (FEM) erm{\"o}glichen. Die Methoden der 3D Schnittplanung an computergrafischen Modellen werden analysiert und eine 3D Osteotomieplanung an polygonalen Sch{\"a}delmodellen entwickelt, die es erm{\"o}glicht, intuitiv durch Definition von Schnittlinien am 3D Knochenmodell, eine den chirurgischen Anforderungen entsprechende Schnittplanung unter Ber{\"u}cksichtigung von Risikostrukturen durchzuf{\"u}hren. Separierte Knochensegmente lassen sich im Anschluss interaktiv umpositionieren und die resultierende Gesamtanordnung hinsichtlich einer funktionellen Rehabilitation bewerten. Aufgrund des in dieser Arbeit gew{\"a}hlten, physikalisch basierten Modellierungsansatzes kann unter Ber{\"u}cksichtigung des gesamten Weichgewebevolumens aus der Knochenverlagerung direkt die resultierende Gesichtsform berechnet werden. Dies wird anhand von 13 exemplarischen Fallstudien anschaulich demonstriert, wobei die Prognosequalit{\"a}t mittels postoperativer Fotografien und postoperativer CT-Daten {\"u}berpr{\"u}ft und belegt wird. Die Arbeit wird mit einem Ausblick auf erweiterte Modellierungsans{\"a}tze und einem Konzept f{\"u}r eine integrierte, klinisch einsetzbare Planungsumgebung abgeschlossen.}, language = {de} } @incollection{ZachowHahnLange2010, author = {Zachow, Stefan and Hahn, Horst and Lange, Thomas}, title = {Computerassistierte Chirugieplanung}, series = {Computerassistierte Chirurgie}, booktitle = {Computerassistierte Chirurgie}, editor = {Schlag, Peter and Eulenstein, Sebastian and Lange, Thomas}, publisher = {Elsevier}, pages = {119 -- 149}, year = {2010}, language = {en} } @inproceedings{JoachimskyAmbellanZachow, author = {Joachimsky, Robert and Ambellan, Felix and Zachow, Stefan}, title = {Computerassistierte Auswahl und Platzierung von interpositionalen Spacern zur Behandlung fr{\"u}her Gonarthrose}, 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-65321}, pages = {106 -- 111}, abstract = {Degenerative Gelenkerkrankungen, wie die Osteoarthrose, sind ein h{\"a}ufiges Krankheitsbild unter {\"a}lteren Erwachsenen. Hierbei verringert sich u.a. der Gelenkspalt aufgrund degenerierten Knorpels oder gesch{\"a}digter Menisci. Ein in den Gelenkspalt eingebrachter interpositionaler Spacer soll die mit der Osteoarthrose einhergehende verringerte Gelenkkontaktfl{\"a}che erh{\"o}hen und so der teilweise oder vollst{\"a}ndige Gelenkersatz hinausgez{\"o}gert oder vermieden werden. In dieser Arbeit pr{\"a}sentieren wir eine Planungssoftware f{\"u}r die Auswahl und Positionierung eines interpositionalen Spacers am Patientenmodell. Auf einer MRT-basierten Bildsegmentierung aufbauend erfolgt eine geometrische Rekonstruktion der 3D-Anatomie des Kniegelenks. Anhand dieser wird der Gelenkspalt bestimmt, sowie ein Spacer ausgew{\"a}hlt und algorithmisch vorpositioniert. Die Positionierung des Spacers ist durch den Benutzer jederzeit interaktiv anpassbar. F{\"u}r jede Positionierung eines Spacers wird ein Fitness-Wert zur Knieanatomie des jeweiligen Patienten berechnet und den Nutzern R{\"u}ckmeldung hinsichtlich Passgenauigkeit gegeben. Die Software unterst{\"u}tzt somit als Entscheidungshilfe die behandelnden {\"A}rzte bei der patientenspezifischen Spacerauswahl.}, language = {de} } @misc{JoachimskyAmbellanZachow, author = {Joachimsky, Robert and Ambellan, Felix and Zachow, Stefan}, title = {Computerassistierte Auswahl und Platzierung von interpositionalen Spacern zur Behandlung fr{\"u}her Gonarthrose}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-66064}, abstract = {Degenerative Gelenkerkrankungen, wie die Osteoarthrose, sind ein h{\"a}ufiges Krankheitsbild unter {\"a}lteren Erwachsenen. Hierbei verringert sich u.a. der Gelenkspalt aufgrund degenerierten Knorpels oder gesch{\"a}digter Menisci. Ein in den Gelenkspalt eingebrachter interpositionaler Spacer soll die mit der Osteoarthrose einhergehende verringerte Gelenkkontaktfl{\"a}che erh{\"o}hen und so der teilweise oder vollst{\"a}ndige Gelenkersatz hinausgez{\"o}gert oder vermieden werden. In dieser Arbeit pr{\"a}sentieren wir eine Planungssoftware f{\"u}r die Auswahl und Positionierung eines interpositionalen Spacers am Patientenmodell. Auf einer MRT-basierten Bildsegmentierung aufbauend erfolgt eine geometrische Rekonstruktion der 3D-Anatomie des Kniegelenks. Anhand dieser wird der Gelenkspalt bestimmt, sowie ein Spacer ausgew{\"a}hlt und algorithmisch vorpositioniert. Die Positionierung des Spacers ist durch den Benutzer jederzeit interaktiv anpassbar. F{\"u}r jede Positionierung eines Spacers wird ein Fitness-Wert zur Knieanatomie des jeweiligen Patienten berechnet und den Nutzern R{\"u}ckmeldung hinsichtlich Passgenauigkeit gegeben. Die Software unterst{\"u}tzt somit als Entscheidungshilfe die behandelnden {\"A}rzte bei der patientenspezifischen Spacerauswahl.}, language = {de} } @article{HierlZachowWollnyetal.2004, author = {Hierl, Thomas and Zachow, Stefan and Wollny, Gert and Berti, Guntram and Schmidt, Jens-Georg and Fingberg, Jochen}, title = {Computer-based simulation in distraction osteogenesis}, series = {Proc. of 3rd Int. Oxford Distraction Symposium of the Craniofacial Skeleton}, journal = {Proc. of 3rd Int. Oxford Distraction Symposium of the Craniofacial Skeleton}, pages = {33 -- 34}, year = {2004}, language = {en} } @article{ZachowHegeDeuflhard2006, author = {Zachow, Stefan and Hege, Hans-Christian and Deuflhard, Peter}, title = {Computer assisted planning in cranio-maxillofacial surgery}, series = {Journal of Computing and Information Technology}, volume = {14(1)}, journal = {Journal of Computing and Information Technology}, pages = {53 -- 64}, year = {2006}, 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} } @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}, series = {Journal of biomechanics}, volume = {45}, journal = {Journal of biomechanics}, number = {13}, doi = {10.1016/j.jbiomech.2012.06.004}, pages = {2215 -- 21}, year = {2012}, language = {en} } @article{Zachow, author = {Zachow, Stefan}, title = {Computational Planning in Facial Surgery}, series = {Facial Plastic Surgery}, volume = {31}, journal = {Facial Plastic Surgery}, number = {5}, doi = {10.1055/s-0035-1564717}, pages = {446 -- 462}, abstract = {This article reflects the research of the last two decades in computational planning for cranio-maxillofacial surgery. Model-guided and computer-assisted surgery planning has tremendously developed due to ever increasing computational capabilities. Simulators for education, planning, and training of surgery are often compared with flight simulators, where maneuvers are also trained to reduce a possible risk of failure. Meanwhile, digital patient models can be derived from medical image data with astonishing accuracy and thus can serve for model surgery to derive a surgical template model that represents the envisaged result. Computerized surgical planning approaches, however, are often still explorative, meaning that a surgeon tries to find a therapeutic concept based on his or her expertise using computational tools that are mimicking real procedures. Future perspectives of an improved computerized planning may be that surgical objectives will be generated algorithmically by employing mathematical modeling, simulation, and optimization techniques. Planning systems thus act as intelligent decision support systems. However, surgeons can still use the existing tools to vary the proposed approach, but they mainly focus on how to transfer objectives into reality. Such a development may result in a paradigm shift for future surgery planning.}, language = {en} } @article{SiqueiraRodriguesSchmidtIsraeletal., author = {Siqueira Rodrigues, Lucas and Schmidt, Timo Torsten and Israel, Johann Habakuk and Nyakatura, John and Zachow, Stefan and Kosch, Thomas}, title = {Comparing the Effects of Visual, Haptic, and Visuohaptic Encoding on Memory Retention of Digital Objects in Virtual Reality}, abstract = {Although Virtual Reality (VR) has undoubtedly improved human interaction with 3D data, users still face difficulties retaining important details of complex digital objects in preparation for physical tasks. To address this issue, we evaluated the potential of visuohaptic integration to improve the memorability of virtual objects in immersive visualizations. In a user study (N=20), participants performed a delayed match-to-sample task where they memorized stimuli of visual, haptic, or visuohaptic encoding conditions. We assessed performance differences between the conditions through error rates and response time. We found that visuohaptic encoding significantly improved memorization accuracy compared to unimodal visual and haptic conditions. Our analysis indicates that integrating haptics into immersive visualizations enhances the memorability of digital objects. We discuss its implications for the optimal encoding design in VR applications that assist professionals who need to memorize and recall virtual objects in their daily work.}, language = {en} } @article{LemanisZachowHoffmann, author = {Lemanis, Robert and Zachow, Stefan and Hoffmann, Ren{\´e}}, title = {Comparative cephalopod shell strength and the role of septum morphology on stress distribution}, series = {PeerJ}, volume = {4}, journal = {PeerJ}, doi = {10.7717/peerj.2434}, pages = {e2434}, abstract = {The evolution of complexly folded septa in ammonoids has long been a controversial topic. Explanations of the function of these folded septa can be divided into physiological and mechanical hypotheses with the mechanical functions tending to find widespread support. The complexity of the cephalopod shell has made it difficult to directly test the mechanical properties of these structures without oversimplification of the septal morphology or extraction of a small sub-domain. However, the power of modern finite element analysis now permits direct testing of mechanical hypothesis on complete, empirical models of the shells taken from computed tomographic data. Here we compare, for the first time using empirical models, the capability of the shells of extant Nautilus pompilius, Spirula spirula, and the extinct ammonite Cadoceras sp. to withstand hydrostatic pressure and point loads. Results show hydrostatic pressure imparts highest stress on the final septum with the rest of the shell showing minimal compression. S. spirula shows the lowest stress under hydrostatic pressure while N. pompilius shows the highest stress. Cadoceras sp. shows the development of high stress along the attachment of the septal saddles with the shell wall. Stress due to point loads decreases when the point force is directed along the suture as opposed to the unsupported chamber wall. Cadoceras sp. shows the greatest decrease in stress between the point loads compared to all other models. Greater amplitude of septal flutes corresponds with greater stress due to hydrostatic pressure; however, greater amplitude decreases the stress magnitude of point loads directed along the suture. In our models, sutural complexity does not predict greater resistance to hydrostatic pressure but it does seem to increase resistance to point loads, such as would be from predators. This result permits discussion of palaeoecological reconstructions on the basis of septal morphology. We further suggest that the ratio used to characterize septal morphology in the septal strength index and in calculations of tensile strength of nacre are likely insufficient. A better understanding of the material properties of cephalopod nacre may allow the estimation of maximum depth limits of shelled cephalopods through finite element analysis.}, 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{AkbariShandizBoulosSavarssonetal.2017, 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}, series = {Journal of Engineering in Medicine}, volume = {232}, journal = {Journal of Engineering in Medicine}, number = {1}, doi = {10.1177/0954411917743274}, pages = {67 -- 79}, year = {2017}, 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{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}, series = {Int. J. of Computer Assisted Radiology and Surgery}, journal = {Int. J. of Computer Assisted Radiology and Surgery}, publisher = {Springer}, pages = {165 -- 167}, year = {2006}, language = {en} } @article{AlHajjSahuLamardetal., author = {Al Hajj, Hassan and Sahu, Manish and Lamard, Mathieu and Conze, Pierre-Henri and Roychowdhury, Soumali and Hu, Xiaowei and Marsalkaite, Gabija and Zisimopoulos, Odysseas and Dedmari, Muneer Ahmad and Zhao, Fenqiang and Prellberg, Jonas and Galdran, Adrian and Araujo, Teresa and Vo, Duc My and Panda, Chandan and Dahiya, Navdeep and Kondo, Satoshi and Bian, Zhengbing and Bialopetravicius, Jonas and Qiu, Chenghui and Dill, Sabrina and Mukhopadyay, Anirban and Costa, Pedro and Aresta, Guilherme and Ramamurthy, Senthil and Lee, Sang-Woong and Campilho, Aurelio and Zachow, Stefan and Xia, Shunren and Conjeti, Sailesh and Armaitis, Jogundas and Heng, Pheng-Ann and Vahdat, Arash and Cochener, Beatrice and Quellec, Gwenole}, title = {CATARACTS: Challenge on Automatic Tool Annotation for cataRACT Surgery}, series = {Medical Image Analysis}, volume = {52}, journal = {Medical Image Analysis}, number = {2}, publisher = {Elsevier}, doi = {10.1016/j.media.2018.11.008}, pages = {24 -- 41}, abstract = {Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected, the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.}, language = {en} } @article{SteinmannBartschZachowetal.2008, author = {Steinmann, Alexander and Bartsch, Peter and Zachow, Stefan and Hildebrandt, Thomas}, title = {Breathing Easily: Simulation of airflow in human noses can become a useful rhinosurgery planning tool}, series = {ANSYS Advantage}, volume = {Vol. II, No. 1}, journal = {ANSYS Advantage}, pages = {30 -- 31}, year = {2008}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2002, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Biomechanisches Modell zur Absch{\"a}tzung der individuellen Gesichtsmimik}, series = {Proc.of Workshop Bildverarbeitung f{\"u}r die Medizin (BVM)}, booktitle = {Proc.of Workshop Bildverarbeitung f{\"u}r die Medizin (BVM)}, editor = {Meiler, M. and Saupe, D. and Krugel, F. and Handels, H. and Lehmann, T.}, address = {Leipzig, Germany}, pages = {25 -- 28}, year = {2002}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2002, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Biomechanical modeling of individual facial emotion expressions}, series = {Proc. of Visualization, Imaging, and Image Processing (VIIP)}, booktitle = {Proc. of Visualization, Imaging, and Image Processing (VIIP)}, address = {Malaga, Spain}, pages = {7 -- 11}, year = {2002}, language = {en} } @article{ZinserZachowSailer2013, author = {Zinser, Max and Zachow, Stefan and Sailer, Hermann}, title = {Bimaxillary "rotation advancement" procedures in patients with obstructive sleep apnea: A 3-dimensional airway analysis of morphological changes}, series = {International Journal of Oral \& Maxillofacial Surgery}, volume = {42}, journal = {International Journal of Oral \& Maxillofacial Surgery}, number = {5}, doi = {10.1016/j.ijom.2012.08.002}, pages = {569 -- 578}, year = {2013}, language = {en} } @inproceedings{DornheimBornZachowetal.2008, author = {Dornheim, Jana and Born, Silvia and Zachow, Stefan and Gessat, Michael and Wellein, Daniela and Strauß, Gero and Preim, Bernhard and Bartz, Dirk}, title = {Bildanalyse, Visualisierung und Modellerstellung f{\"u}r die Implantatplanung im Mittelohr}, series = {Proc. of Simulation and Visualization 2008}, booktitle = {Proc. of Simulation and Visualization 2008}, editor = {Hauser, Helwig}, pages = {139 -- 154}, year = {2008}, language = {en} } @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} } @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{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} } @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{SeimKainmuellerHelleretal.2009, author = {Seim, Heiko and Kainm{\"u}ller, Dagmar and Heller, Markus O. and Zachow, Stefan and Hege, Hans-Christian}, title = {Automatic Extraction of Anatomical Landmarks from Medical Image Data: An Evaluation of Different Methods}, series = {Proc. of IEEE Int. Symposium on Biomedical Imaging (ISBI)}, booktitle = {Proc. of IEEE Int. Symposium on Biomedical Imaging (ISBI)}, address = {Boston, MA, USA}, pages = {538 -- 541}, year = {2009}, 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{SchenklMuggenthalerHubigetal.2017, author = {Schenkl, Sebastian and Muggenthaler, Holger and Hubig, Michael and Erdmann, Bodo and Weiser, Martin and Zachow, Stefan and Heinrich, Andreas and G{\"u}ttler, Felix Victor and Teichgr{\"a}ber, Ulf and Mall, Gita}, title = {Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis}, series = {International Journal of Legal Medicine}, volume = {131}, journal = {International Journal of Legal Medicine}, number = {3}, doi = {doi:10.1007/s00414-016-1523-0}, pages = {699 -- 712}, year = {2017}, abstract = {Temperature based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex, but allow a higher accuracy of death time estimation as in principle all relevant cooling mechanisms can be taken into account. Here, a complete work flow for finite element based cooling simulation models is presented. The following steps are demonstrated on CT-phantoms: • CT-scan • Segmentation of the CT images for thermodynamically relevant features of individual geometries • Conversion of the segmentation result into a Finite Element (FE) simulation model • Computation of the model cooling curve • Calculation of the cooling time For the first time in FE-based cooling time estimation the steps from the CT image over segmentation to FE model generation are semi-automatically performed. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using different CTphantoms. Some of the CT phantoms thermodynamic material parameters had to be experimentally determined via independent experiments. Moreover the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.}, 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} } @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{AmbellanTackEhlkeetal., 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 (Supplementary Material)}, series = {Medical Image Analysis}, volume = {52}, journal = {Medical Image Analysis}, number = {2}, doi = {10.12752/4.ATEZ.1.0}, pages = {109 -- 118}, abstract = {We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging 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 of 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 of the SKI10 challenge. For the first time, an accuracy equivalent to the inter-observer variability of human readers has been 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 made 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 statistical anatomical knowledge via SSMs with the localized classification via CNNs results in a state-of-the-art segmentation method for knee bones and cartilage from MRI data.}, language = {en} } @inproceedings{AmbellanTackEhlkeetal., 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}, series = {Medical Imaging with Deep Learning}, booktitle = {Medical Imaging with Deep Learning}, abstract = {We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging, 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 method is evaluated on data of the MICCAI grand challenge "Segmentation of Knee Images 2010". For the first time an accuracy equivalent to the inter-observer variability of human readers has been achieved in this challenge. Moreover, the quality of the proposed method is thoroughly assessed using various measures for 507 manual segmentations of bone and cartilage, and 88 additional manual segmentations of cartilage. Our method yields sub-voxel accuracy. In conclusion, combining of anatomical knowledge using SSMs with localized classification via CNNs results in a state-of-the-art segmentation method.}, language = {en} } @misc{AmbellanTackEhlkeetal., 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}, 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} } @article{AmbellanTackEhlkeetal., 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}, series = {Medical Image Analysis}, volume = {52}, journal = {Medical Image Analysis}, number = {2}, doi = {10.1016/j.media.2018.11.009}, pages = {109 -- 118}, abstract = {We present a method for the automated segmentation of knee bones and cartilage from magnetic resonance imaging 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 of 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 of the SKI10 challenge. For the first time, an accuracy equivalent to the inter-observer variability of human readers has been 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 made 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 statistical anatomical knowledge via SSMs with the localized classification via CNNs results in a state-of-the-art segmentation method for knee bones and cartilage from MRI data.}, 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{EhlkeHeylandMaerdianetal., author = {Ehlke, Moritz and Heyland, Mark and M{\"a}rdian, Sven and Duda, Georg and Zachow, Stefan}, title = {Assessing the Relative Positioning of an Osteosynthesis Plate to the Patient-Specific Femoral Shape from Plain 2D Radiographs}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-54268}, abstract = {We present a novel method to derive the surface distance of an osteosynthesis plate w.r.t. the patient­specific surface of the distal femur based on 2D X­ray images. Our goal is to study from clinical data, how the plate­to­bone distance affects bone healing. The patient­specific 3D shape of the femur is, however, seldom recorded for cases of femoral osteosynthesis since this typically requires Computed Tomography (CT), which comes at high cost and radiation dose. Our method instead utilizes two postoperative X­ray images to derive the femoral shape and thus can be applied on radiographs that are taken in clinical routine for follow­up. First, the implant geometry is used as a calibration object to relate the implant and the individual X­ray images spatially in a virtual X­ray setup. In a second step, the patient­specific femoral shape and pose are reconstructed in the virtual setup by fitting a deformable statistical shape and intensity model (SSIM) to the images. The relative positioning between femur and implant is then assessed in terms of displacement between the reconstructed 3D shape of the femur and the plate. A preliminary evaluation based on 4 cadaver datasets shows that the method derives the plate­to­bone distance with a mean absolute error of less than 1mm and a maximum error of 4.7 mm compared to ground truth from CT. We believe that the approach presented in this paper constitutes a meaningful tool to elucidate the effect of implant positioning on fracture healing.}, language = {en} } @inproceedings{EhlkeHeylandMaerdianetal., author = {Ehlke, Moritz and Heyland, Mark and M{\"a}rdian, Sven and Duda, Georg and Zachow, Stefan}, title = {Assessing the relative positioning of an osteosynthesis plate to the patient-specific femoral shape from plain 2D radiographs}, series = {Proceedings of the 15th Annual Meeting of CAOS-International (CAOS)}, booktitle = {Proceedings of the 15th Annual Meeting of CAOS-International (CAOS)}, abstract = {We present a novel method to derive the surface distance of an osteosynthesis plate w.r.t. the patient­specific surface of the distal femur based on 2D X­ray images. Our goal is to study from clinical data, how the plate­to­bone distance affects bone healing. The patient­specific 3D shape of the femur is, however, seldom recorded for cases of femoral osteosynthesis since this typically requires Computed Tomography (CT), which comes at high cost and radiation dose. Our method instead utilizes two postoperative X­ray images to derive the femoral shape and thus can be applied on radiographs that are taken in clinical routine for follow­up. First, the implant geometry is used as a calibration object to relate the implant and the individual X­ray images spatially in a virtual X­ray setup. In a second step, the patient­specific femoral shape and pose are reconstructed in the virtual setup by fitting a deformable statistical shape and intensity model (SSIM) to the images. The relative positioning between femur and implant is then assessed in terms of displacement between the reconstructed 3D shape of the femur and the plate. A preliminary evaluation based on 4 cadaver datasets shows that the method derives the plate­to­bone distance with a mean absolute error of less than 1mm and a maximum error of 4.7 mm compared to ground truth from CT. We believe that the approach presented in this paper constitutes a meaningful tool to elucidate the effect of implant positioning on fracture healing.}, language = {en} } @misc{KoberSaderZeilhoferetal., author = {Kober, Cornelia and Sader, Robert and Zeilhofer, Hans-Florian and Prohaska, Steffen and Zachow, Stefan and Deuflhard, Peter}, title = {Anisotrope Materialmodellierung f{\"u}r den menschlichen Unterkiefer}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-6574}, number = {01-31}, abstract = {Im Rahmen der biomechanischen Simulation kn{\"o}cherner Organe ist die Frage nach einer befriedigenden Materialbeschreibung nach wie vor ungel{\"o}st. Computertomographische Datens{\"a}tze liefern eine r{\"a}umliche Verteilung der (R{\"o}ntgen-)Dichte und erm{\"o}glichen damit eine gute Darstellung der individuellen Geometrie. Weiter k{\"o}nnen die verschiedenen Materialbestandteile des Knochens, Spongiosa und Kortikalis, voneinander getrennt werden. Aber die richtungsab{\"a}ngige Information der Materialanisotropie ist verloren. In dieser Arbeit wird ein Ansatz f{\"u}r eine anisotrope Materialbeschreibung vorgestellt, die es erm{\"o}glicht, den Einfluss der individuellen kn{\"o}chernen Struktur auf das makroskopische Materialverhalten abzusch{\"a}tzen.}, language = {de} } @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}, series = {Med Biol Eng Comput.}, volume = {42(2)}, journal = {Med Biol Eng Comput.}, doi = {10.1007/BF02344627}, pages = {167 -- 170}, year = {2004}, language = {en} } @misc{SahuSzengelMukhopadhyayetal., author = {Sahu, Manish and Szengel, Angelika and Mukhopadhyay, Anirban and Zachow, Stefan}, title = {Analyzing laparoscopic cholecystectomy with deep learning: automatic detection of surgical tools and phases}, series = {28th International Congress of the European Association for Endoscopic Surgery (EAES)}, journal = {28th International Congress of the European Association for Endoscopic Surgery (EAES)}, abstract = {Motivation: The ever-rising volume of patients, high maintenance cost of operating rooms and time consuming analysis of surgical skills are fundamental problems that hamper the practical training of the next generation of surgeons. The hospitals prefer to keep the surgeons busy in real operations over training young surgeons for obvious economic reasons. One fundamental need in surgical training is the reduction of the time needed by the senior surgeon to review the endoscopic procedures performed by the young surgeon while minimizing the subjective bias in evaluation. The unprecedented performance of deep learning ushers the new age of data-driven automatic analysis of surgical skills. Method: Deep learning is capable of efficiently analyzing thousands of hours of laparoscopic video footage to provide an objective assessment of surgical skills. However, the traditional end-to-end setting of deep learning (video in, skill assessment out) is not explainable. Our strategy is to utilize the surgical process modeling framework to divide the surgical process into understandable components. This provides the opportunity to employ deep learning for superior yet automatic detection and evaluation of several aspects of laparoscopic cholecystectomy such as surgical tool and phase detection. We employ ZIBNet for the detection of surgical tool presence. ZIBNet employs pre-processing based on tool usage imbalance, a transfer learned 50-layer residual network (ResNet-50) and temporal smoothing. To encode the temporal evolution of tool usage (over the entire video sequence) that relates to the surgical phases, Long Short Term Memory (LSTM) units are employed with long-term dependency. Dataset: We used CHOLEC 80 dataset that consists of 80 videos of laparoscopic cholecystectomy performed by 13 surgeons, divided equally for training and testing. In these videos, up to three different tools (among 7 types of tools) can be present in a frame. Results: The mean average precision of the detection of all tools is 93.5 ranging between 86.8 and 99.3, a significant improvement (p <0.01) over the previous state-of-the-art. We observed that less frequent tools like Scissors, Irrigator, Specimen Bag etc. are more related to phase transitions. The overall precision (recall) of the detection of all surgical phases is 79.6 (81.3). Conclusion: While this is not the end goal for surgical skill analysis, the development of such a technological platform is essential toward a data-driven objective understanding of surgical skills. In future, we plan to investigate surgeon-in-the-loop analysis and feedback for surgical skill analysis.}, 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{SiqueiraRodriguesNyakaturaZachowetal., author = {Siqueira Rodrigues, Lucas and Nyakatura, John and Zachow, Stefan and Israel, Johann Habakuk}, title = {An Immersive Virtual Paleontology Application}, series = {13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022}, booktitle = {13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022}, doi = {10.1007/978-3-031-06249-0}, pages = {478 -- 481}, abstract = {Virtual paleontology studies digital fossils through data analysis and visualization systems. The discipline is growing in relevance for the evident advantages of non-destructive imaging techniques over traditional paleontological methods, and it has made significant advancements during the last few decades. However, virtual paleontology still faces a number of technological challenges, amongst which are interaction shortcomings of image segmentation applications. Whereas automated segmentation methods are seldom applicable to fossil datasets, manual exploration of these specimens is extremely time-consuming as it impractically delves into three-dimensional data through two-dimensional visualization and interaction means. This paper presents an application that employs virtual reality and haptics to virtual paleontology in order to evolve its interaction paradigms and address some of its limitations. We provide a brief overview of the challenges faced by virtual paleontology practitioners, a description of our immersive virtual paleontology prototype, and the results of a heuristic evaluation of our design.}, language = {en} } @article{vonTycowiczAmbellanMukhopadhyayetal., author = {von Tycowicz, Christoph and Ambellan, Felix and Mukhopadhyay, Anirban and Zachow, Stefan}, title = {An Efficient Riemannian Statistical Shape Model using Differential Coordinates}, series = {Medical Image Analysis}, volume = {43}, journal = {Medical Image Analysis}, number = {1}, doi = {10.1016/j.media.2017.09.004}, pages = {1 -- 9}, abstract = {We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as elements of a Lie group thereby endowing our shape space with a non-Euclidean structure. A key advantage of our framework is that statistics in a manifold shape space becomes numerically tractable improving performance by several orders of magnitude over state-of-the-art. We show that our Riemannian model is well suited for the identification of intra-population variability as well as inter-population differences. In particular, we demonstrate the superiority of the proposed model in experiments on specificity and generalization ability. We further derive a statistical shape descriptor that outperforms the standard Euclidean approach in terms of shape-based classification of morphological disorders.}, language = {en} } @inproceedings{AmbellanZachowvonTycowicz, author = {Ambellan, Felix and Zachow, Stefan and von Tycowicz, Christoph}, title = {An as-invariant-as-possible GL+(3)-based Statistical Shape Model}, series = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, volume = {11846}, booktitle = {Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA)}, publisher = {Springer}, doi = {10.1007/978-3-030-33226-6_23}, pages = {219 -- 228}, abstract = {We describe a novel nonlinear statistical shape model basedon differential coordinates viewed as elements of GL+(3). We adopt an as-invariant-as possible framework comprising a bi-invariant Lie group mean and a tangent principal component analysis based on a unique GL+(3)-left-invariant, O(3)-right-invariant metric. Contrary to earlier work that equips the coordinates with a specifically constructed group structure, our method employs the inherent geometric structure of the group-valued data and therefore features an improved statistical power in identifying shape differences. We demonstrate this in experiments on two anatomical datasets including comparison to the standard Euclidean as well as recent state-of-the-art nonlinear approaches to statistical shape modeling.}, language = {en} } @misc{AmbellanZachowvonTycowicz, author = {Ambellan, Felix and Zachow, Stefan and von Tycowicz, Christoph}, title = {An as-invariant-as-possible GL+(3)-based Statistical Shape Model}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-74566}, abstract = {We describe a novel nonlinear statistical shape model basedon differential coordinates viewed as elements of GL+(3). We adopt an as-invariant-as possible framework comprising a bi-invariant Lie group mean and a tangent principal component analysis based on a unique GL+(3)-left-invariant, O(3)-right-invariant metric. Contrary to earlier work that equips the coordinates with a specifically constructed group structure, our method employs the inherent geometric structure of the group-valued data and therefore features an improved statistical power in identifying shape differences. We demonstrate this in experiments on two anatomical datasets including comparison to the standard Euclidean as well as recent state-of-the-art nonlinear approaches to statistical shape modeling.}, 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} }