@inproceedings{ZachowHierlErdmann2004, author = {Zachow, Stefan and Hierl, Thomas and Erdmann, Bodo}, title = {{\"U}ber die Genauigkeit einer 3D Weichgewebepr{\"a}diktion in der MKG-Cirurgie}, series = {Workshop 'Bildverarbeitung f{\"u}r die Medizin' (BVM)}, booktitle = {Workshop 'Bildverarbeitung f{\"u}r die Medizin' (BVM)}, address = {Berlin, Germany}, pages = {75 -- 79}, year = {2004}, language = {en} } @inproceedings{SiqueiraRodriguesRiehmZachowetal., author = {Siqueira Rodrigues, Lucas and Riehm, Felix and Zachow, Stefan and Israel, Johann Habakuk}, title = {VoxSculpt: An Open-Source Voxel Library for Tomographic Volume Sculpting in Virtual Reality}, series = {2023 9th International Conference on Virtual Reality (ICVR), Xianyang, China, 2023}, booktitle = {2023 9th International Conference on Virtual Reality (ICVR), Xianyang, China, 2023}, doi = {10.1109/ICVR57957.2023.10169420}, pages = {515 -- 523}, abstract = {Manual processing of tomographic data volumes, such as interactive image segmentation in medicine or paleontology, is considered a time-consuming and cumbersome endeavor. Immersive volume sculpting stands as a potential solution to improve its efficiency and intuitiveness. However, current open-source software solutions do not yield the required performance and functionalities. We address this issue by contributing a novel open-source game engine voxel library that supports real-time immersive volume sculpting. Our design leverages GPU instancing, parallel computing, and a chunk-based data structure to optimize collision detection and rendering. We have implemented features that enable fast voxel interaction and improve precision. Our benchmark evaluation indicates that our implementation offers a significant improvement over the state-of-the-art and can render and modify millions of visible voxels while maintaining stable performance for real-time interaction in virtual reality.}, language = {en} } @inproceedings{HierlWollnyZachowetal.2002, author = {Hierl, Thomas and Wollny, Gert and Zachow, Stefan and Kl{\"o}ppel, Rainer}, title = {Visualisierung von Knochen und Weichteilver{\"a}nderungen in der Distraktionsosteogenese des Mittelgesichtes}, series = {Proc. 10. Jahrestagung der Deutschen Gesellschaft f{\"u}r Sch{\"a}delbasischirurgie}, booktitle = {Proc. 10. Jahrestagung der Deutschen Gesellschaft f{\"u}r Sch{\"a}delbasischirurgie}, address = {Heidelberg}, pages = {111 -- 116}, year = {2002}, language = {en} } @inproceedings{RammVictoriaMorilloTodtetal.2013, author = {Ramm, Heiko and Victoria Morillo, Oscar Salvador and Todt, Ingo and Schirmacher, Hartmut and Ernst, Arneborg and Zachow, Stefan and Lamecker, Hans}, title = {Visual Support for Positioning Hearing Implants}, series = {Proceedings of the 12th annual meeting of the CURAC society}, booktitle = {Proceedings of the 12th annual meeting of the CURAC society}, editor = {Freysinger, Wolfgang}, pages = {116 -- 120}, year = {2013}, language = {en} } @misc{RammMorilloVictoriaTodtetal., author = {Ramm, Heiko and Morillo Victoria, Oscar Salvador and Todt, Ingo and Schirmacher, Hartmut and Ernst, Arneborg and Zachow, Stefan and Lamecker, Hans}, title = {Visual Support for Positioning Hearing Implants}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42495}, abstract = {We present a software planning tool that provides intuitive visual feedback for finding suitable positions of hearing implants in the human temporal bone. After an automatic reconstruction of the temporal bone anatomy the tool pre-positions the implant and allows the user to adjust its position interactively with simple 2D dragging and rotation operations on the bone's surface. During this procedure, visual elements like warning labels on the implant or color encoded bone density information on the bone geometry provide guidance for the determination of a suitable fit.}, language = {en} } @article{ZachowMuiggHildebrandtetal.2009, author = {Zachow, Stefan and Muigg, Philipp and Hildebrandt, Thomas and Doleisch, Helmut and Hege, Hans-Christian}, title = {Visual Exploration of Nasal Airflow}, series = {IEEE Transactions on Visualization and Computer Graphics}, volume = {15}, journal = {IEEE Transactions on Visualization and Computer Graphics}, number = {8}, doi = {10.1109/TVCG.2009.198}, pages = {1407 -- 1414}, year = {2009}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Virtual Fibers: A Robust Approach for Muscle Simulation}, series = {IX Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)}, booktitle = {IX Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)}, address = {Pula, Croatia}, pages = {961 -- 964}, year = {2001}, language = {en} } @article{SekuboyinaHusseiniBayatetal., author = {Sekuboyina, Anjany and Husseini, Malek E. and Bayat, Amirhossein and L{\"o}ffler, Maximilian and Liebl, Hans and Li, Hongwei and Tetteh, Giles and Kukačka, Jan and Payer, Christian and Štern, Darko and Urschler, Martin and Chen, Maodong and Cheng, Dalong and Lessmann, Nikolas and Hu, Yujin and Wang, Tianfu and Yang, Dong and Xu, Daguang and Ambellan, Felix and Amiranashvili, Tamaz and Ehlke, Moritz and Lamecker, Hans and Lehnert, Sebastian and Lirio, Marilia and de Olaguer, Nicol{\´a}s P{\´e}rez and Ramm, Heiko and Sahu, Manish and Tack, Alexander and Zachow, Stefan and Jiang, Tao and Ma, Xinjun and Angerman, Christoph and Wang, Xin and Brown, Kevin and Kirszenberg, Alexandre and Puybareau, {\´E}lodie and Chen, Di and Bai, Yiwei and Rapazzo, Brandon H. and Yeah, Timyoas and Zhang, Amber and Xu, Shangliang and Hou, Feng and He, Zhiqiang and Zeng, Chan and Xiangshang, Zheng and Liming, Xu and Netherton, Tucker J. and Mumme, Raymond P. and Court, Laurence E. and Huang, Zixun and He, Chenhang and Wang, Li-Wen and Ling, Sai Ho and Huynh, L{\^e} Duy and Boutry, Nicolas and Jakubicek, Roman and Chmelik, Jiri and Mulay, Supriti and Sivaprakasam, Mohanasankar and Paetzold, Johannes C. and Shit, Suprosanna and Ezhov, Ivan and Wiestler, Benedikt and Glocker, Ben and Valentinitsch, Alexander and Rempfler, Markus and Menze, Bj{\"o}rn H. and Kirschke, Jan S.}, title = {VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images}, series = {Medical Image Analysis}, volume = {73}, journal = {Medical Image Analysis}, doi = {10.1016/j.media.2021.102166}, abstract = {Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.}, language = {en} } @article{SekuboyinaBayatHusseinietal., author = {Sekuboyina, Anjany and Bayat, Amirhossein and Husseini, Malek E. and L{\"o}ffler, Maximilian and Li, Hongwei and Tetteh, Giles and Kukačka, Jan and Payer, Christian and Štern, Darko and Urschler, Martin and Chen, Maodong and Cheng, Dalong and Lessmann, Nikolas and Hu, Yujin and Wang, Tianfu and Yang, Dong and Xu, Daguang and Ambellan, Felix and Amiranashvili, Tamaz and Ehlke, Moritz and Lamecker, Hans and Lehnert, Sebastian and Lirio, Marilia and de Olaguer, Nicol{\´a}s P{\´e}rez and Ramm, Heiko and Sahu, Manish and Tack, Alexander and Zachow, Stefan and Jiang, Tao and Ma, Xinjun and Angerman, Christoph and Wang, Xin and Wei, Qingyue and Brown, Kevin and Wolf, Matthias and Kirszenberg, Alexandre and Puybareau, {\´E}lodie and Valentinitsch, Alexander and Rempfler, Markus and Menze, Bj{\"o}rn H. and Kirschke, Jan S.}, title = {VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images}, series = {arXiv}, journal = {arXiv}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Validierung eines linear elastischen Modells f{\"u}r die Weichgewebesimulation in der Mund-Kiefer-Gesichtschirurgie}, series = {Bildverarbeitung f{\"u}r die Medizin (BVM)}, booktitle = {Bildverarbeitung f{\"u}r die Medizin (BVM)}, address = {L{\"u}beck, Germany}, pages = {57 -- 61}, year = {2001}, language = {en} } @article{WilsonAnglinAmbellanetal., author = {Wilson, David and Anglin, Carolyn and Ambellan, Felix and Grewe, Carl Martin and Tack, Alexander and Lamecker, Hans and Dunbar, Michael and Zachow, Stefan}, title = {Validation of three-dimensional models of the distal femur created from surgical navigation point cloud data for intraoperative and postoperative analysis of total knee arthroplasty}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {12}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {12}, publisher = {Springer}, doi = {10.1007/s11548-017-1630-5}, pages = {2097 -- 2105}, abstract = {Purpose: Despite the success of total knee arthroplasty there continues to be a significant proportion of patients who are dissatisfied. One explanation may be a shape mismatch between pre and post-operative distal femurs. The purpose of this study was to investigate a method to match a statistical shape model (SSM) to intra-operatively acquired point cloud data from a surgical navigation system, and to validate it against the pre-operative magnetic resonance imaging (MRI) data from the same patients. Methods: A total of 10 patients who underwent navigated total knee arthroplasty also had an MRI scan less than 2 months pre-operatively. The standard surgical protocol was followed which included partial digitization of the distal femur. Two different methods were employed to fit the SSM to the digitized point cloud data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). The available MRI data were manually segmented and the reconstructed three-dimensional surfaces used as ground truth against which the statistical shape model fit was compared. Results: For both approaches, the difference between the statistical shape model-generated femur and the surface generated from MRI segmentation averaged less than 1.7 mm, with maximum errors occurring in less clinically important areas. Conclusion: The results demonstrated good correspondence with the distal femoral morphology even in cases of sparse data sets. Application of this technique will allow for measurement of mismatch between pre and post-operative femurs retrospectively on any case done using the surgical navigation system and could be integrated into the surgical navigation unit to provide real-time feedback.}, language = {en} } @misc{WilsonBuecherGreweetal., author = {Wilson, David and B{\"u}cher, Pia and Grewe, Carl Martin and Anglin, Carolyn and Zachow, Stefan and Michael, Dunbar}, title = {Validation of Three Dimensional Models of the Distal Femur Created from Surgical Navigation Point Cloud Data}, series = {15th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery (CAOS)}, journal = {15th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery (CAOS)}, language = {en} } @misc{WilsonBuecherGreweetal., author = {Wilson, David and B{\"u}cher, Pia and Grewe, Carl Martin and Mocanu, Valentin and Anglin, Carolyn and Zachow, Stefan and Dunbar, Michael}, title = {Validation of Three Dimensional Models of the Distal Femur Created from Surgical Navigation Data}, series = {Orthopedic Research Society Annual Meeting}, journal = {Orthopedic Research Society Annual Meeting}, address = {Las Vegas, Nevada}, language = {en} } @inproceedings{GladilinZachowDeuflhardetal.2001, author = {Gladilin, Evgeny and Zachow, Stefan and Deuflhard, Peter and Hege, Hans-Christian}, title = {Validation of a Linear Elastic Model for Soft Tissue Simulation in Craniofacial Surgery}, series = {Proc. SPIE Medical Imaging 2001}, volume = {4319}, booktitle = {Proc. SPIE Medical Imaging 2001}, editor = {Mun, Seong}, address = {San Diego, USA}, doi = {10.1117/12.428061}, pages = {27 -- 35}, year = {2001}, language = {en} } @inproceedings{EstacioEhlkeTacketal., author = {Estacio, Laura and Ehlke, Moritz and Tack, Alexander and Castro-Gutierrez, Eveling and Lamecker, Hans and Mora, Rensso and Zachow, Stefan}, title = {Unsupervised Detection of Disturbances in 2D Radiographs}, series = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)}, booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)}, doi = {10.1109/ISBI48211.2021.9434091}, pages = {367 -- 370}, abstract = {We present a method based on a generative model for detection of disturbances such as prosthesis, screws, zippers, and metals in 2D radiographs. The generative model is trained in an unsupervised fashion using clinical radiographs as well as simulated data, none of which contain disturbances. Our approach employs a latent space consistency loss which has the benefit of identifying similarities, and is enforced to reconstruct X-rays without disturbances. In order to detect images with disturbances, an anomaly score is computed also employing the Frechet distance between the input X-ray and the reconstructed one using our generative model. Validation was performed using clinical pelvis radiographs. We achieved an AUC of 0.77 and 0.83 with clinical and synthetic data, respectively. The results demonstrated a good accuracy of our method for detecting outliers as well as the advantage of utilizing synthetic data.}, language = {en} } @article{ZachowSteinmannHildebrandtetal.2007, author = {Zachow, Stefan and Steinmann, Alexander and Hildebrandt, Thomas and Heppt, Werner}, title = {Understanding nasal airflow via CFD simulation and visualization}, series = {Proc. Computer Aided Surgery around the Head}, journal = {Proc. Computer Aided Surgery around the Head}, pages = {173 -- 176}, year = {2007}, language = {en} } @misc{WeiserErdmannSchenkletal.2017, author = {Weiser, Martin and Erdmann, Bodo and Schenkl, Sebastian and Muggenthaler, Holger and Hubig, Michael and Mall, Gita and Zachow, Stefan}, title = {Uncertainty in Temperature-Based Determination of Time of Death}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-63818}, year = {2017}, abstract = {Temperature-based estimation of time of death (ToD) can be per- formed either with the help of simple phenomenological models of corpse cooling or with detailed mechanistic (thermodynamic) heat transfer mod- els. The latter are much more complex, but allow a higher accuracy of ToD estimation as in principle all relevant cooling mechanisms can be taken into account. The potentially higher accuracy depends on the accuracy of tissue and environmental parameters as well as on the geometric resolution. We in- vestigate the impact of parameter variations and geometry representation on the estimated ToD based on a highly detailed 3D corpse model, that has been segmented and geometrically reconstructed from a computed to- mography (CT) data set, differentiating various organs and tissue types. From that we identify the most crucial parameters to measure or estimate, and obtain a local uncertainty quantifcation for the ToD.}, language = {en} } @article{WeiserErdmannSchenkletal., author = {Weiser, Martin and Erdmann, Bodo and Schenkl, Sebastian and Muggenthaler, Holger and Hubig, Michael and Mall, Gita and Zachow, Stefan}, title = {Uncertainty in Temperature-Based Determination of Time of Death}, series = {Heat and Mass Transfer}, volume = {54}, journal = {Heat and Mass Transfer}, number = {9}, publisher = {Springer}, doi = {10.1007/s00231-018-2324-4}, pages = {2815 -- 2826}, abstract = {Temperature-based estimation of time of death (ToD) can be per- formed either with the help of simple phenomenological models of corpse cooling or with detailed mechanistic (thermodynamic) heat transfer mod- els. The latter are much more complex, but allow a higher accuracy of ToD estimation as in principle all relevant cooling mechanisms can be taken into account. The potentially higher accuracy depends on the accuracy of tissue and environmental parameters as well as on the geometric resolution. We in- vestigate the impact of parameter variations and geometry representation on the estimated ToD based on a highly detailed 3D corpse model, that has been segmented and geometrically reconstructed from a computed to- mography (CT) data set, differentiating various organs and tissue types.}, language = {en} } @inproceedings{KraemerMaggioniTycowiczetal., author = {Kr{\"a}mer, Martin and Maggioni, Marta and Tycowicz, Christoph von and Brisson, Nick and Zachow, Stefan and Duda, Georg and Reichenbach, J{\"u}rgen}, title = {Ultra-short echo-time (UTE) imaging of the knee with curved surface reconstruction-based extraction of the patellar tendon}, series = {ISMRM (International Society for Magnetic Resonance in Medicine), 26th Annual Meeting 2018, Paris, France}, booktitle = {ISMRM (International Society for Magnetic Resonance in Medicine), 26th Annual Meeting 2018, Paris, France}, abstract = {Due to very short T2 relaxation times, imaging of tendons is typically performed using ultra-short echo-time (UTE) acquisition techniques. In this work, we combined an echo-train shifted multi-echo 3D UTE imaging sequence with a 3D curved surface reconstruction to virtually extract the patellar tendon from an acquired 3D UTE dataset. Based on the analysis of the acquired multi-echo data, a T2* relaxation time parameter map was calculated and interpolated to the curved surface of the patellar tendon.}, language = {en} } @article{ZeilhoferZachowFairleyetal.2000, author = {Zeilhofer, Hans-Florian and Zachow, Stefan and Fairley, Jeffrey and Sader, Robert and Deuflhard, Peter}, title = {Treatment Planning and Simulation in Craniofacial Surgery with Virtual Reality Techiques}, series = {Journal of Cranio-Maxillofacial Surgery}, volume = {28 (Suppl. 1)}, journal = {Journal of Cranio-Maxillofacial Surgery}, pages = {82}, year = {2000}, language = {en} }