TY - JOUR A1 - Hierl, Thomas A1 - Zachow, Stefan A1 - Wollny, Gert A1 - Berti, Guntram A1 - Schmidt, Jens-Georg A1 - Fingberg, Jochen T1 - Concepts of computer-based simulation in orthognathic surgery JF - Journal of Cranio-Maxillofacial Surgery 32 Suppl. 1 Y1 - 2004 SP - 81 EP - 82 ER - TY - JOUR A1 - Zachow, Stefan A1 - Lamecker, Hans A1 - Zöckler, Maja A1 - Haberl, Ernst T1 - Computergestützte Planung zur chirurgischen Korrektur von frühkindlichen Schädelfehlbildungen (Craniosynostosen) JF - Face 02/09, Int. Mag. of Orofacial Esthetics, Oemus Journale Leipzig Y1 - 2009 SP - 48 EP - 53 ER - TY - JOUR A1 - Zachow, Stefan A1 - Deuflhard, Peter T1 - Computergestützte Planung in der kraniofazialen Chirurgie JF - Face 01/08, Int. Mag. of Orofacial Esthetics Y1 - 2008 SP - 43 EP - 49 PB - Oemus Journale Leipzig ER - TY - CHAP A1 - Ramm, Heiko A1 - Zachow, Stefan ED - Niederlag, Wolfgang ED - Lemke, Heinz ED - Peitgen, Heinz-Otto ED - Lehrach, Hans T1 - Computergestützte Planung für die individuelle Implantatversorgung T2 - Health Academy Y1 - 2012 VL - 16 SP - 145 EP - 158 ER - TY - CHAP A1 - Zachow, Stefan A1 - Hege, Hans-Christian A1 - Deuflhard, Peter T1 - Computergestützte Operationsplanung in der Gesichtschirurgie T2 - Proc. VDE Kongress 2004 - Innovationen für Menschen, Band 2, Fachtagungsberichte DGBMT - GMM - GMA Y1 - 2004 SP - 53 EP - 58 ER - TY - THES A1 - Zachow, Stefan T1 - Computergestützte 3D Osteotomieplanung in der Mund-Kiefer-Gesichtschirurgie unter Berücksichtigung der räumlichen Weichgewebeanordnung T1 - Computer assisted 3D osteotomy planning in cranio-maxillofacial surgery under consideration of facial soft tissue arrangement N2 - In der Arbeit wird die computergestützte Planung von chirurgisch gesetzten Knochenfrakturen bzw. Knochenschnitten (sogenannten Osteotomien) an dreidimensionalen, computergrafischen Schädelmodellen, sowie die Umpositionierung separierter knöcherner 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 durchgeführt und diese in Hinblick auf Funktion und Ästhetik bewertet werden kann. Unterschiedliche Strategien können dabei erprobt und in ihrer Auswirkung erfasst werden. Dazu wird ein methodischer Ansatz vorgestellt, der zum einen die chirurgische Planung im Vergleich zu existierenden Ansätzen deutlich verbessert und zum anderen eine robuste Weichgewebeprognose, durch den Einsatz geeigneter Planungsmodelle und eines physikalisch basierten Weichgewebemodells unter Nutzung numerischer Lösungsverfahren in die Planung integriert. Die Visualisierung der Planungsergebnisse erlaubt sowohl eine anschauliche und überzeugende, präoperative Patientenaufklärung, als auch die Demonstration möglicher Vorgehensweisen und deren Auswirkungen für die chirurgische Ausbildung. Ferner ergänzen die Planungsdaten die Falldokumentation und liefern einen Beitrag zur Qualitätssicherung. 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 Überblick über entsprechende Vorarbeiten zur computergestützten 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) ermöglichen. Die Methoden der 3D Schnittplanung an computergrafischen Modellen werden analysiert und eine 3D Osteotomieplanung an polygonalen Schädelmodellen entwickelt, die es ermöglicht, intuitiv durch Definition von Schnittlinien am 3D Knochenmodell, eine den chirurgischen Anforderungen entsprechende Schnittplanung unter Berücksichtigung von Risikostrukturen durchzuführen. Separierte Knochensegmente lassen sich im Anschluss interaktiv umpositionieren und die resultierende Gesamtanordnung hinsichtlich einer funktionellen Rehabilitation bewerten. Aufgrund des in dieser Arbeit gewählten, physikalisch basierten Modellierungsansatzes kann unter Berücksichtigung des gesamten Weichgewebevolumens aus der Knochenverlagerung direkt die resultierende Gesichtsform berechnet werden. Dies wird anhand von 13 exemplarischen Fallstudien anschaulich demonstriert, wobei die Prognosequalität mittels postoperativer Fotografien und postoperativer CT-Daten überprüft und belegt wird. Die Arbeit wird mit einem Ausblick auf erweiterte Modellierungsansätze und einem Konzept für eine integrierte, klinisch einsetzbare Planungsumgebung abgeschlossen. N2 - In cranio-maxillofacial surgery, physicians are often faced with skeletal malformations that require complex bone relocations. Especially in severe cases of congenital dysgnathia (misalignment of upper and lower jaw) or hemifacial microsomia (asymmetric bone and tissue development), where multiple bone segments are to be mobilized and relocated simultaneously and in relation to each other, careful preoperative planning is mandatory. At present in clinical routine not all possible strategies can be planned and assessed with regard to functional rehabilitation. Moreover, the aesthetic outcome, i.e. the postoperative facial appearance, can only be estimated by a surgeon's experience and hardly communicated to the patient. On this account, a preoperative planning of complex osteotomies with bone relocations on a computerized model of a patient's head, including a reliable three-dimensional prediction and visualization of the post-surgical facial appearance is a highly appreciated possibility cranio-maxillofacial surgeons are longing for. This work, being performed at Zuse Institute Berlin (ZIB), addresses such a computer based 3D~surgery planning. A processing pipeline has been established and a simulation environment has been developed on basis of the software Amira, enabling a surgeon to perform bone cuts and bone rearrangements in an intuitive manner on virtual patient models. In addition, a prediction of the patients' postoperative appearance according to the relocated bone can be simulated and visualized realistically. For a meaningful planning of surgical procedures, anatomically correct patient models providing all relevant details are reconstructed from tomographic data with high fidelity. These patient models reliably represent bony structures as well as the facial soft tissue. Unstructured volumetric grids of the soft tissue are generated for a fast and efficient numerical solution of partial differential equations, describing tissue deformation on the foundation of 3D elastomechanics. The planning of osteotomies (bone cuts) for the mobilization and relocation of bone segments is performed in accordance to the planning on basis of life size replicas of a patient's skull, i.e. stereolitographic models. Osteotomy lines can be drawn on top of the polygonal planning models using suitable input devices. After evaluation of the consequence of a planned cut with regard to vulnerable inner structures (nerves, teeth etc.) the model is separated accordingly. A relocation of bone segments can be performed unrestrictedly in 3D or restricted to a translation or rotation within arbitrarily chosen planes under consideration of cephalometric guidelines. Bone and tooth collisions can be evaluated for functional analysis or orthodontic treatment planning with possible integration of digitized dental plaster casts. As a result of the preoperative planning, a single transformation matrix, encoding translation and rotation, or a sequence of such matrices are provided for each bone segment. Both the osteotomy paths and the transformation parameters can finally be used for intra-operative navigation. In the course of the planning, the relocated positions of bone segments serve as an input for the simulation of the resulting soft tissue deformation. Since bone and surrounding soft tissue share common boundaries that are either fixed or translocated, the resulting configuration of the entire tissue volume can be computed from the given boundary displacements by numerical minimization of the internal strain energy on basis of a biomechanical model, using a finite-element approach. In collaboration with different surgeons and hospitals more than 25 treatments have been accompanied by preoperative planning so far ranging from mandibular and midfacial hypoplasia to complex hemifacial microsomia. 13 of these cases are presented within this work. Simulation results were validated on the basis of photographs as well as of postoperative CT data, showing a good correlation between simulation and postoperative outcome. Further aspects of improving the modeling approach are discussed. It has been demonstrated that 3D~osteotomy planning on virtual patient models can be performed intuitively, and that 3D~tissue deformation for cranio-maxillofacial osteotomy planning can be predicted numerically without using heuristic ratios. It can be stated that by using 3D~planning software, a surgeon gains a better spatial understanding of complex dysplasia, and the 3D~soft tissue prediction gives an additional criterion for the assessment of the planned strategy. It turned out that, especially in complex cases such as hemifacial microsomia or for decisions bet­ween mono- and bimaxillary advancements, a 3D~planning aid is extremely helpful. The conclusion is, that images and animations created within the planning phase provide a valuable planning criterion for maxillofacial surgeons as well as a demonstrative information for patients and their relatives, thus greatly enhancing patient information, as well as surgical education. All data that result from the planning are also important for documentation and quality assurance. 3D osteotomy planning, including soft tissue prediction, likely will become a new paradigm of plastic and reconstructive surgery planning in the future. An assortment of results can be found under: http://www.zib.de/visual/medical/projects KW - MKG-Chirurgie KW - Mund-Kiefer-Gesichtschirurgie KW - Therapieplanung KW - Osteotomie KW - Weichgewebeprädiktion KW - computer assisted surgery KW - therapy planning KW - osteotomy KW - soft tissue prediction KW - CAS Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-10432 SN - 3899631986 ER - TY - CHAP A1 - Zachow, Stefan A1 - Hahn, Horst A1 - Lange, Thomas ED - Schlag, Peter ED - Eulenstein, Sebastian ED - Lange, Thomas T1 - Computerassistierte Chirugieplanung T2 - Computerassistierte Chirurgie Y1 - 2010 SP - 119 EP - 149 PB - Elsevier ER - TY - CHAP A1 - Joachimsky, Robert A1 - Ambellan, Felix A1 - Zachow, Stefan T1 - Computerassistierte Auswahl und Platzierung von interpositionalen Spacern zur Behandlung früher Gonarthrose T2 - Proceedings of the Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) N2 - Degenerative Gelenkerkrankungen, wie die Osteoarthrose, sind ein häufiges Krankheitsbild unter älteren Erwachsenen. Hierbei verringert sich u.a. der Gelenkspalt aufgrund degenerierten Knorpels oder geschädigter Menisci. Ein in den Gelenkspalt eingebrachter interpositionaler Spacer soll die mit der Osteoarthrose einhergehende verringerte Gelenkkontaktfläche erhöhen und so der teilweise oder vollständige Gelenkersatz hinausgezögert oder vermieden werden. In dieser Arbeit präsentieren wir eine Planungssoftware für 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 ausgewählt und algorithmisch vorpositioniert. Die Positionierung des Spacers ist durch den Benutzer jederzeit interaktiv anpassbar. Für jede Positionierung eines Spacers wird ein Fitness-Wert zur Knieanatomie des jeweiligen Patienten berechnet und den Nutzern Rückmeldung hinsichtlich Passgenauigkeit gegeben. Die Software unterstützt somit als Entscheidungshilfe die behandelnden Ärzte bei der patientenspezifischen Spacerauswahl. KW - Osteoarthrose KW - Kniegelenk KW - Medizinische Planung KW - Visualisierung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65321 VL - 16 SP - 106 EP - 111 ER - TY - GEN A1 - Joachimsky, Robert A1 - Ambellan, Felix A1 - Zachow, Stefan T1 - Computerassistierte Auswahl und Platzierung von interpositionalen Spacern zur Behandlung früher Gonarthrose N2 - Degenerative Gelenkerkrankungen, wie die Osteoarthrose, sind ein häufiges Krankheitsbild unter älteren Erwachsenen. Hierbei verringert sich u.a. der Gelenkspalt aufgrund degenerierten Knorpels oder geschädigter Menisci. Ein in den Gelenkspalt eingebrachter interpositionaler Spacer soll die mit der Osteoarthrose einhergehende verringerte Gelenkkontaktfläche erhöhen und so der teilweise oder vollständige Gelenkersatz hinausgezögert oder vermieden werden. In dieser Arbeit präsentieren wir eine Planungssoftware für 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 ausgewählt und algorithmisch vorpositioniert. Die Positionierung des Spacers ist durch den Benutzer jederzeit interaktiv anpassbar. Für jede Positionierung eines Spacers wird ein Fitness-Wert zur Knieanatomie des jeweiligen Patienten berechnet und den Nutzern Rückmeldung hinsichtlich Passgenauigkeit gegeben. Die Software unterstützt somit als Entscheidungshilfe die behandelnden Ärzte bei der patientenspezifischen Spacerauswahl. T3 - ZIB-Report - 17-72 KW - Osteoarthrose KW - Kniegelenk KW - Medizinische Planung KW - Visualisierung Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-66064 SN - 1438-0064 ER - TY - JOUR A1 - Hierl, Thomas A1 - Zachow, Stefan A1 - Wollny, Gert A1 - Berti, Guntram A1 - Schmidt, Jens-Georg A1 - Fingberg, Jochen T1 - Computer-based simulation in distraction osteogenesis JF - Proc. of 3rd Int. Oxford Distraction Symposium of the Craniofacial Skeleton Y1 - 2004 SP - 33 EP - 34 ER - TY - JOUR A1 - Zachow, Stefan A1 - Hege, Hans-Christian A1 - Deuflhard, Peter T1 - Computer assisted planning in cranio-maxillofacial surgery JF - Journal of Computing and Information Technology Y1 - 2006 VL - 14(1) SP - 53 EP - 64 ER - TY - THES A1 - Zachow, Stefan T1 - Computer assisted osteotomy planning in cranio-maxillofacial surgery under consideration of facial soft tissue changes T2 - Computergestützte Osteotomieplanung in der Mund-Kiefer-Gesichtschirurgie unter Berücksichtigung der räumlichen Weichgewebeanordnung Y1 - 2005 UR - www.dr.hut-verlag.de/titelMedizininformatik.html ER - TY - JOUR A1 - Ho, Karen A1 - Saevarsson, Stefan A1 - Ramm, Heiko A1 - Lieck, Robert A1 - Zachow, Stefan A1 - Sharma, Gulshan A1 - Rex, Erica A1 - Amiri, Shahram A1 - Wu, Barnabas A1 - Leumann, Andre A1 - Anglin, Carolyn T1 - Computed tomography analysis of knee pose and geometry before and after total knee arthroplasty JF - Journal of biomechanics Y1 - 2012 UR - http://www.ncbi.nlm.nih.gov/pubmed/22796002 U6 - https://doi.org/10.1016/j.jbiomech.2012.06.004 VL - 45 IS - 13 SP - 2215 EP - 21 ER - TY - JOUR A1 - Zachow, Stefan T1 - Computational Planning in Facial Surgery JF - Facial Plastic Surgery N2 - 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. Y1 - 2015 U6 - https://doi.org/10.1055/s-0035-1564717 VL - 31 IS - 5 SP - 446 EP - 462 ER - TY - JOUR A1 - Siqueira Rodrigues, Lucas A1 - Schmidt, Timo Torsten A1 - Israel, Johann Habakuk A1 - Nyakatura, John A1 - Zachow, Stefan A1 - Kosch, Thomas T1 - Comparing the Effects of Visual, Haptic, and Visuohaptic Encoding on Memory Retention of Digital Objects in Virtual Reality N2 - 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. Y1 - 2024 ER - TY - JOUR A1 - Lemanis, Robert A1 - Zachow, Stefan A1 - Hoffmann, René T1 - Comparative cephalopod shell strength and the role of septum morphology on stress distribution JF - PeerJ N2 - 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. Y1 - 2016 U6 - https://doi.org/10.7717/peerj.2434 VL - 4 SP - e2434 ER - TY - JOUR A1 - Brüning, Jan A1 - Hildebrandt, Thomas A1 - Heppt, Werner A1 - Schmidt, Nora A1 - Lamecker, Hans A1 - Szengel, Angelika A1 - Amiridze, Natalja A1 - Ramm, Heiko A1 - Bindernagel, Matthias A1 - Zachow, Stefan A1 - Goubergrits, Leonid T1 - Characterization of the Airflow within an Average Geometry of the Healthy Human Nasal Cavity JF - Scientific Reports N2 - 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. Y1 - 2020 UR - https://rdcu.be/b2irD U6 - https://doi.org/10.1038/s41598-020-60755-3 VL - 3755 IS - 10 ER - TY - JOUR A1 - Akbari Shandiz, Mohsen A1 - Boulos, Paul A1 - Sævarsson, Stefan A1 - Ramm, Heiko A1 - Fu, Chun Kit A1 - Miller, Stephen A1 - Zachow, Stefan A1 - Anglin, Carolyn T1 - Changes in Knee Shape and Geometry Resulting from Total Knee Arthroplasty JF - Journal of Engineering in Medicine N2 - 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. Y1 - 2018 UR - http://journals.sagepub.com/eprint/ZVgNrNESA9EjIcaFWSjb/full U6 - https://doi.org/10.1177/0954411917743274 VL - 232 IS - 1 SP - 67 EP - 79 ER - TY - JOUR A1 - Zachow, Stefan A1 - Steinmann, Alexander A1 - Hildebrandt, Thomas A1 - Weber, Rainer A1 - Heppt, Werner T1 - CFD simulation of nasal airflow: Towards treatment planning for functional rhinosurgery JF - Int. J. of Computer Assisted Radiology and Surgery Y1 - 2006 SP - 165 EP - 167 PB - Springer ER - TY - JOUR A1 - Al Hajj, Hassan A1 - Sahu, Manish A1 - Lamard, Mathieu A1 - Conze, Pierre-Henri A1 - Roychowdhury, Soumali A1 - Hu, Xiaowei A1 - Marsalkaite, Gabija A1 - Zisimopoulos, Odysseas A1 - Dedmari, Muneer Ahmad A1 - Zhao, Fenqiang A1 - Prellberg, Jonas A1 - Galdran, Adrian A1 - Araujo, Teresa A1 - Vo, Duc My A1 - Panda, Chandan A1 - Dahiya, Navdeep A1 - Kondo, Satoshi A1 - Bian, Zhengbing A1 - Bialopetravicius, Jonas A1 - Qiu, Chenghui A1 - Dill, Sabrina A1 - Mukhopadyay, Anirban A1 - Costa, Pedro A1 - Aresta, Guilherme A1 - Ramamurthy, Senthil A1 - Lee, Sang-Woong A1 - Campilho, Aurelio A1 - Zachow, Stefan A1 - Xia, Shunren A1 - Conjeti, Sailesh A1 - Armaitis, Jogundas A1 - Heng, Pheng-Ann A1 - Vahdat, Arash A1 - Cochener, Beatrice A1 - Quellec, Gwenole T1 - CATARACTS: Challenge on Automatic Tool Annotation for cataRACT Surgery JF - Medical Image Analysis N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1016/j.media.2018.11.008 N1 - Best paper award - Computer Graphics Night 2020 (TU Darmstadt) VL - 52 IS - 2 SP - 24 EP - 41 PB - Elsevier ER - TY - JOUR A1 - Steinmann, Alexander A1 - Bartsch, Peter A1 - Zachow, Stefan A1 - Hildebrandt, Thomas T1 - Breathing Easily: Simulation of airflow in human noses can become a useful rhinosurgery planning tool JF - ANSYS Advantage Y1 - 2008 VL - Vol. II, No. 1 SP - 30 EP - 31 ER - TY - CHAP A1 - Gladilin, Evgeny A1 - Zachow, Stefan A1 - Deuflhard, Peter A1 - Hege, Hans-Christian ED - Meiler, M. ED - Saupe, D. ED - Krugel, F. ED - Handels, H. ED - Lehmann, T. T1 - Biomechanisches Modell zur Abschätzung der individuellen Gesichtsmimik T2 - Proc.of Workshop Bildverarbeitung für die Medizin (BVM) Y1 - 2002 SP - 25 EP - 28 CY - Leipzig, Germany ER - TY - CHAP A1 - Gladilin, Evgeny A1 - Zachow, Stefan A1 - Deuflhard, Peter A1 - Hege, Hans-Christian T1 - Biomechanical modeling of individual facial emotion expressions T2 - Proc. of Visualization, Imaging, and Image Processing (VIIP) Y1 - 2002 SP - 7 EP - 11 CY - Malaga, Spain ER - TY - JOUR A1 - Zinser, Max A1 - Zachow, Stefan A1 - Sailer, Hermann T1 - Bimaxillary "rotation advancement" procedures in patients with obstructive sleep apnea: A 3-dimensional airway analysis of morphological changes JF - International Journal of Oral & Maxillofacial Surgery Y1 - 2013 U6 - https://doi.org/10.1016/j.ijom.2012.08.002 VL - 42 IS - 5 SP - 569 EP - 578 ER - TY - CHAP A1 - Dornheim, Jana A1 - Born, Silvia A1 - Zachow, Stefan A1 - Gessat, Michael A1 - Wellein, Daniela A1 - Strauß, Gero A1 - Preim, Bernhard A1 - Bartz, Dirk ED - Hauser, Helwig T1 - Bildanalyse, Visualisierung und Modellerstellung für die Implantatplanung im Mittelohr T2 - Proc. of Simulation and Visualization 2008 Y1 - 2008 SP - 139 EP - 154 ER - TY - CHAP A1 - Lamecker, Hans A1 - Kainmüller, Dagmar A1 - Seim, Heiko A1 - Zachow, Stefan T1 - Automatische 3D Rekonstruktion des Unterkiefers und der Mandibulärnerven auf Basis dentaler Bildgebung T2 - Proc. BMT, Biomed Tech Y1 - 2010 VL - 55 (Suppl. 1) SP - 35 EP - 36 PB - Walter de Gruyter-Verlag ER - TY - CHAP A1 - Seim, Heiko A1 - Kainmüller, Dagmar A1 - Heller, Markus O. A1 - Lamecker, Hans A1 - Zachow, Stefan A1 - Hege, Hans-Christian T1 - Automatic Segmentation of the Pelvic Bones from CT Data Based on a Statistical Shape Model T2 - Eurographics Workshop on Visual Computing for Biomedicine (VCBM) Y1 - 2008 SP - 93 EP - 100 CY - Delft, Netherlands ER - TY - JOUR A1 - Lamecker, Hans A1 - Zachow, Stefan A1 - Wittmers, Antonia A1 - Weber, Britta A1 - Hege, Hans-Christian A1 - Elsholtz, Barbara A1 - Stiller, Michael T1 - Automatic segmentation of mandibles in low-dose CT-data JF - Int. J. Computer Assisted Radiology and Surgery Y1 - 2006 VL - 1(1) SP - 393 EP - 395 ER - TY - CHAP A1 - Kainmüller, Dagmar A1 - Lamecker, Hans A1 - Seim, Heiko A1 - Zinser, Max A1 - Zachow, Stefan ED - Yang, Guang-Zhong ED - J. Hawkes, David ED - Rueckert, Daniel ED - Noble, J. Alison ED - J. Taylor, Chris T1 - Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data T2 - Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI) Y1 - 2009 SP - 76 EP - 83 CY - London, UK ER - TY - CHAP A1 - Seim, Heiko A1 - Kainmüller, Dagmar A1 - Heller, Markus O. A1 - Zachow, Stefan A1 - Hege, Hans-Christian T1 - Automatic Extraction of Anatomical Landmarks from Medical Image Data: An Evaluation of Different Methods T2 - Proc. of IEEE Int. Symposium on Biomedical Imaging (ISBI) Y1 - 2009 SP - 538 EP - 541 CY - Boston, MA, USA ER - TY - CHAP A1 - Nguyen, The Duy A1 - Lamecker, Hans A1 - Kainmüller, Dagmar A1 - Zachow, Stefan ED - Ayache, Nicholas ED - Delingette, Hervé ED - Golland, Polina ED - Mori, Kensaku T1 - Automatic Detection and Classification of Teeth in CT Data T2 - Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI) Y1 - 2012 VL - 7510 SP - 609 EP - 616 ER - TY - JOUR A1 - Schenkl, Sebastian A1 - Muggenthaler, Holger A1 - Hubig, Michael A1 - Erdmann, Bodo A1 - Weiser, Martin A1 - Zachow, Stefan A1 - Heinrich, Andreas A1 - Güttler, Felix Victor A1 - Teichgräber, Ulf A1 - Mall, Gita T1 - Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis JF - International Journal of Legal Medicine N2 - 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. KW - temperature based death time estimation KW - finite element method KW - CT segmentation KW - sensitivity analysis Y1 - 2017 U6 - https://doi.org/doi:10.1007/s00414-016-1523-0 VL - 131 IS - 3 SP - 699 EP - 712 ER - TY - JOUR A1 - Nguyen, The Duy A1 - Kainmüller, Dagmar A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Automatic bone and tooth detection for CT-based dental implant planning JF - Int. J. Computer Assisted Radiology and Surgery Y1 - 2012 VL - 7, Supplement 1 IS - 1 SP - 293 EP - 294 PB - Springer ER - TY - JOUR A1 - Pimentel, Pedro A1 - Szengel, Angelika A1 - Ehlke, Moritz A1 - Lamecker, Hans A1 - Zachow, Stefan A1 - Estacio, Laura A1 - Doenitz, Christian A1 - Ramm, Heiko ED - Li, Jianning ED - Egger, Jan T1 - Automated Virtual Reconstruction of Large Skull Defects using Statistical Shape Models and Generative Adversarial Networks BT - First Challenge, AutoImplant 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings JF - Towards the Automatization of Cranial Implant Design in Cranioplasty N2 - 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. Y1 - 2020 U6 - https://doi.org/10.1007/978-3-030-64327-0_3 N1 - Best Paper Award VL - 12439 SP - 16 EP - 27 PB - Springer International Publishing ET - 1 ER - TY - GEN A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Ehlke, Moritz A1 - Zachow, Stefan T1 - Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative (Supplementary Material) T2 - Medical Image Analysis N2 - 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. Y1 - 2019 U6 - https://doi.org/10.12752/4.ATEZ.1.0 N1 - OAI-ZIB dataset VL - 52 IS - 2 SP - 109 EP - 118 ER - TY - CHAP A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Ehlke, Moritz A1 - Zachow, Stefan T1 - Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative T2 - Medical Imaging with Deep Learning N2 - 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. Y1 - 2018 ER - TY - GEN A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Ehlke, Moritz A1 - Zachow, Stefan T1 - Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative N2 - 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. T3 - ZIB-Report - 19-06 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-72704 SN - 1438-0064 N1 - Innovation Excellence Award 2020 ER - TY - JOUR A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Ehlke, Moritz A1 - Zachow, Stefan T1 - Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative JF - Medical Image Analysis N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1016/j.media.2018.11.009 VL - 52 IS - 2 SP - 109 EP - 118 ER - TY - JOUR A1 - Li, Jianning A1 - Pimentel, Pedro A1 - Szengel, Angelika A1 - Ehlke, Moritz A1 - Lamecker, Hans A1 - Zachow, Stefan A1 - Estacio, Laura A1 - Doenitz, Christian A1 - Ramm, Heiko A1 - Shi, Haochen A1 - Chen, Xiaojun A1 - Matzkin, Franco A1 - Newcombe, Virginia A1 - Ferrante, Enzo A1 - Jin, Yuan A1 - Ellis, David G. A1 - Aizenberg, Michele R. A1 - Kodym, Oldrich A1 - Spanel, Michal A1 - Herout, Adam A1 - Mainprize, James G. A1 - Fishman, Zachary A1 - Hardisty, Michael R. A1 - Bayat, Amirhossein A1 - Shit, Suprosanna A1 - Wang, Bomin A1 - Liu, Zhi A1 - Eder, Matthias A1 - Pepe, Antonio A1 - Gsaxner, Christina A1 - Alves, Victor A1 - Zefferer, Ulrike A1 - von Campe, Cord A1 - Pistracher, Karin A1 - Schäfer, Ute A1 - Schmalstieg, Dieter A1 - Menze, Bjoern H. A1 - Glocker, Ben A1 - Egger, Jan T1 - AutoImplant 2020 - First MICCAI Challenge on Automatic Cranial Implant Design JF - IEEE Transactions on Medical Imaging N2 - 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. Y1 - 2021 U6 - https://doi.org/10.1109/TMI.2021.3077047 SN - 0278-0062 VL - 40 IS - 9 SP - 2329 EP - 2342 ER - TY - GEN A1 - Ehlke, Moritz A1 - Heyland, Mark A1 - Märdian, Sven A1 - Duda, Georg A1 - Zachow, Stefan T1 - Assessing the Relative Positioning of an Osteosynthesis Plate to the Patient-Specific Femoral Shape from Plain 2D Radiographs N2 - 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. T3 - ZIB-Report - 15-21 KW - 3d-­reconstruction from 2d X­rays KW - statistical shape and intensity models KW - fracture fixation of the distal femur KW - pose estimation Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-54268 SN - 1438-0064 ER - TY - CHAP A1 - Ehlke, Moritz A1 - Heyland, Mark A1 - Märdian, Sven A1 - Duda, Georg A1 - Zachow, Stefan T1 - Assessing the relative positioning of an osteosynthesis plate to the patient-specific femoral shape from plain 2D radiographs T2 - Proceedings of the 15th Annual Meeting of CAOS-International (CAOS) N2 - 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. KW - 3d-­reconstruction from 2d X­rays KW - statistical shape and intensity models KW - fracture fixation of the distal femur KW - pose estimation Y1 - 2015 ER - TY - GEN A1 - Kober, Cornelia A1 - Sader, Robert A1 - Zeilhofer, Hans-Florian A1 - Prohaska, Steffen A1 - Zachow, Stefan A1 - Deuflhard, Peter T1 - Anisotrope Materialmodellierung für den menschlichen Unterkiefer N2 - Im Rahmen der biomechanischen Simulation knöcherner Organe ist die Frage nach einer befriedigenden Materialbeschreibung nach wie vor ungelöst. Computertomographische Datensätze liefern eine räumliche Verteilung der (Röntgen-)Dichte und ermöglichen damit eine gute Darstellung der individuellen Geometrie. Weiter können die verschiedenen Materialbestandteile des Knochens, Spongiosa und Kortikalis, voneinander getrennt werden. Aber die richtungsabängige Information der Materialanisotropie ist verloren. In dieser Arbeit wird ein Ansatz für eine anisotrope Materialbeschreibung vorgestellt, die es ermöglicht, den Einfluss der individuellen knöchernen Struktur auf das makroskopische Materialverhalten abzuschätzen. T3 - ZIB-Report - 01-31 KW - menschlicher Unterkiefer KW - Simulation mit der Methode der finiten Elemente KW - innerer Aufbau des Knochens KW - anisotrope Elastizität Y1 - 2001 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-6574 ER - TY - JOUR A1 - Gladilin, Evgeny A1 - Zachow, Stefan A1 - Deuflhard, Peter A1 - Hege, Hans-Christian T1 - Anatomy- and physics-based facial animation for craniofacial surgery simulations JF - Med Biol Eng Comput. Y1 - 2004 U6 - https://doi.org/10.1007/BF02344627 VL - 42(2) SP - 167 EP - 170 ER - TY - GEN A1 - Sahu, Manish A1 - Szengel, Angelika A1 - Mukhopadhyay, Anirban A1 - Zachow, Stefan T1 - Analyzing laparoscopic cholecystectomy with deep learning: automatic detection of surgical tools and phases T2 - 28th International Congress of the European Association for Endoscopic Surgery (EAES) N2 - 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. Y1 - 2020 UR - https://academy.eaes.eu/eaes/2020/28th/298882/manish.sahu.analyzing.laparoscopic.cholecystectomy.with.deep.learning.html?f=listing%3D0%2Abrowseby%3D8%2Asortby%3D2 ER - TY - GEN A1 - Bindernagel, Matthias A1 - Kainmüller, Dagmar A1 - Ramm, Heiko A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Analysis of inter-individual anatomical shape variations of joint structures T2 - Proc. Int. Society of Computer Assisted Orthopaedic Surgery (CAOS) Y1 - 2012 IS - 210 ER - TY - CHAP A1 - Siqueira Rodrigues, Lucas A1 - Nyakatura, John A1 - Zachow, Stefan A1 - Israel, Johann Habakuk T1 - An Immersive Virtual Paleontology Application T2 - 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022 N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1007/978-3-031-06249-0 SP - 478 EP - 481 ER - TY - JOUR A1 - von Tycowicz, Christoph A1 - Ambellan, Felix A1 - Mukhopadhyay, Anirban A1 - Zachow, Stefan T1 - An Efficient Riemannian Statistical Shape Model using Differential Coordinates JF - Medical Image Analysis N2 - 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. Y1 - 2018 U6 - https://doi.org/10.1016/j.media.2017.09.004 VL - 43 IS - 1 SP - 1 EP - 9 ER - TY - CHAP A1 - Ambellan, Felix A1 - Zachow, Stefan A1 - von Tycowicz, Christoph T1 - An as-invariant-as-possible GL+(3)-based Statistical Shape Model T2 - Proc. 7th MICCAI workshop on Mathematical Foundations of Computational Anatomy (MFCA) N2 - 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. Y1 - 2019 U6 - https://doi.org/10.1007/978-3-030-33226-6_23 VL - 11846 SP - 219 EP - 228 PB - Springer ER - TY - GEN A1 - Ambellan, Felix A1 - Zachow, Stefan A1 - von Tycowicz, Christoph T1 - An as-invariant-as-possible GL+(3)-based Statistical Shape Model N2 - 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. T3 - ZIB-Report - 19-46 KW - Statistical shape analysis KW - Tangent principal component analysis KW - Lie groups KW - Classification KW - Manifold valued statistics Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-74566 SN - 1438-0064 ER - TY - CHAP A1 - Bindernagel, Matthias A1 - Kainmüller, Dagmar A1 - Seim, Heiko A1 - Lamecker, Hans A1 - Zachow, Stefan A1 - Hege, Hans-Christian T1 - An Articulated Statistical Shape Model of the Human Knee T2 - Bildverarbeitung für die Medizin 2011 Y1 - 2011 U6 - https://doi.org/10.1007/978-3-642-19335-4_14 SP - 59 EP - 63 PB - Springer ER -