TY - GEN A1 - Grewe, Carl Martin A1 - Zachow, Stefan ED - Doll, Nikola ED - Bredekamp, Horst ED - Schäffner, Wolfgang T1 - Face to Face-Interface T2 - +ultra. Knowledge & Gestaltung Y1 - 2017 SP - 320 EP - 321 PB - Seemann Henschel ER - TY - JOUR A1 - Hildebrandt, Thomas A1 - Goubergrits, Leonid A1 - Heppt, Werner A1 - Bessler, Stefan A1 - Zachow, Stefan T1 - Evaluation of the Intranasal Flow Field through Computational Fluid Dynamics (CFD) JF - Journal of Facial and Plastic Surgery Y1 - 2013 UR - https://www.thieme-connect.de/DOI/DOI?10.1055/s-0033-1341591 U6 - https://doi.org/10.1055/s-0033-1341591 VL - 29 IS - 2 SP - 93 EP - 98 PB - Thieme ER - TY - CHAP A1 - Siqueira Rodrigues, Lucas A1 - Nyakatura, John A1 - Zachow, Stefan A1 - Israel, Johann Habakuk A1 - Kosch, Thomas T1 - Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images T2 - The 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry N2 - Scientific visualization and tomographic imaging techniques have created unprecedented possibilities for non-destructive analyses of digital specimens in morphology. However, practitioners encounter difficulties retaining critical information from complex tomographic volumes in their workflows. In light of this challenge, we investigated the effectiveness of visuohaptic integration in enhancing memory retention of morphological data. In a within-subjects user study (N=18), participants completed a delayed match-to-sample task, where we compared error rates and response times across visual and visuohaptic sensory modality conditions. Our results indicate that visuohaptic encoding improves the retention of tomographic images, producing significantly reduced error rates and faster response times than its unimodal visual counterpart. Our findings suggest that integrating haptics into scientific visualization interfaces may support professionals in fields such as morphology, where accurate retention of complex spatial data is essential for efficient analysis and decision-making within virtual environments. Y1 - 2024 U6 - https://doi.org/10.1145/3703619.3706055 SP - 1 EP - 10 PB - ACM CY - New York, NY, USA ER - TY - CHAP A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Wilson, Dave A1 - Anglin, Carolyn A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Evaluating two methods for Geometry Reconstruction from Sparse Surgical Navigation Data T2 - Proceedings of the Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) N2 - In this study we investigate methods for fitting a Statistical Shape Model (SSM) to intraoperatively acquired point cloud data from a surgical navigation system. We validate the fitted models against the pre-operatively acquired Magnetic Resonance Imaging (MRI) data from the same patients. We consider a cohort of 10 patients who underwent navigated total knee arthroplasty. As part of the surgical protocol the patients’ distal femurs were partially digitized. All patients had an MRI scan two months pre-operatively. The MRI data were manually segmented and the reconstructed bone surfaces used as ground truth against which the fit was compared. Two methods were used to fit the SSM to the data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). For both approaches, the difference between model fit and ground truth surface averaged less than 1.7 mm and excellent correspondence with the distal femoral morphology can be demonstrated. KW - Total Knee Arthoplasty KW - Sparse Geometry Reconstruction KW - Statistical Shape Models Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-65339 VL - 16 SP - 24 EP - 30 ER - TY - GEN A1 - Ambellan, Felix A1 - Tack, Alexander A1 - Wilson, Dave A1 - Anglin, Carolyn A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Evaluating two methods for Geometry Reconstruction from Sparse Surgical Navigation Data N2 - In this study we investigate methods for fitting a Statistical Shape Model (SSM) to intraoperatively acquired point cloud data from a surgical navigation system. We validate the fitted models against the pre-operatively acquired Magnetic Resonance Imaging (MRI) data from the same patients. We consider a cohort of 10 patients who underwent navigated total knee arthroplasty. As part of the surgical protocol the patients’ distal femurs were partially digitized. All patients had an MRI scan two months pre-operatively. The MRI data were manually segmented and the reconstructed bone surfaces used as ground truth against which the fit was compared. Two methods were used to fit the SSM to the data, based on (1) Iterative Closest Points (ICP) and (2) Gaussian Mixture Models (GMM). For both approaches, the difference between model fit and ground truth surface averaged less than 1.7 mm and excellent correspondence with the distal femoral morphology can be demonstrated. T3 - ZIB-Report - 17-71 KW - Knee Arthroplasty KW - Sparse Geometry Reconstruction KW - Statistical Shape Models Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-66052 SN - 1438-0064 ER - TY - JOUR A1 - Hembus, Jessica A1 - Ambellan, Felix A1 - Zachow, Stefan A1 - Bader, Rainer T1 - Establishment of a rolling-sliding test bench to analyze abrasive wear propagation of different bearing materials for knee implants JF - Applied Sciences N2 - Currently, new materials for knee implants need to be extensively and expensive tested in a knee wear simulator in a realized design. However, using a rolling-sliding test bench, these materials can be examined under the same test conditions but with simplified geometries. In the present study, the test bench was optimized, and forces were adapted to the physiological contact pressure in the knee joint using the available geometric parameters. Various polymers made of polyethylene and polyurethane articulating against test wheels made of cobalt-chromium and aluminum titanate were tested in the test bench using adapted forces based on ISO 14243-1. Polyurethane materials showed distinctly higher wear rates than polyethylene materials and showed inadequate wear resistance for use as knee implant material. Thus, the rolling-sliding test bench is an adaptable test setup for evaluating newly developed bearing materials for knee implants. It combines the advantages of screening and simulator tests and allows testing of various bearing materials under physiological load and tribological conditions of the human knee joint. The wear behavior of different material compositions and the influence of surface geometry and quality can be initially investigated without the need to produce complex implant prototypes of total knee endoprosthesis or interpositional spacers. Y1 - 2021 U6 - https://doi.org/10.3390/app11041886 VL - 11 IS - 4 ER - TY - CHAP A1 - Sahu, Manish A1 - Strömsdörfer, Ronja A1 - Mukhopadhyay, Anirban A1 - Zachow, Stefan T1 - Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation T2 - Proc. Medical Image Computing and Computer Assisted Intervention (MICCAI), Part III N2 - Surgical tool segmentation in endoscopic videos is an important component of computer assisted interventions systems. Recent success of image-based solutions using fully-supervised deep learning approaches can be attributed to the collection of big labeled datasets. However, the annotation of a big dataset of real videos can be prohibitively expensive and time consuming. Computer simulations could alleviate the manual labeling problem, however, models trained on simulated data do not generalize to real data. This work proposes a consistency-based framework for joint learning of simulated and real (unlabeled) endoscopic data to bridge this performance generalization issue. Empirical results on two data sets (15 videos of the Cholec80 and EndoVis'15 dataset) highlight the effectiveness of the proposed Endo-Sim2Real method for instrument segmentation. We compare the segmentation of the proposed approach with state-of-the-art solutions and show that our method improves segmentation both in terms of quality and quantity. Y1 - 2020 U6 - https://doi.org/https://doi.org/10.1007/978-3-030-59716-0_75 VL - 12263 PB - Springer Nature ER - TY - GEN A1 - Ehlke, Moritz A1 - Ramm, Heiko A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Efficient projection and deformation of volumetric shape and intensity models for accurate simulation of X-ray images T2 - Eurographics Workshop on Visual Computing for Biomedicine (NVIDIA best poster award) Y1 - 2012 ER - TY - GEN A1 - Ehlke, Moritz A1 - Ramm, Heiko A1 - Lamecker, Hans A1 - Zachow, Stefan T1 - Efficient projection and deformation of volumetric intensity models for accurate simulation of X-ray images N2 - We present an efficient GPU-based method to generate virtual X-ray images from tetrahedral meshes which are associated with attenuation values. In addition, a novel approach is proposed that performs the model deformation on the GPU. The tetrahedral grids are derived from volumetric statistical shape and intensity models (SSIMs) and describe anatomical structures. Our research targets at reconstructing 3D anatomical shapes by comparing virtual X-ray images generated using our novel approach with clinical data while varying the shape and density of the SSIM in an optimization process. We assume that a deformed SSIM adequately represents an anatomy of interest when the similarity between the virtual and the clinical X-ray image is maximized. The OpenGL implementation presented here generates accurate (virtual) X-ray images at interactive rates, thus qualifying it for its use in the reconstruction process. T3 - ZIB-Report - 12-40 KW - Digitally Reconstructed Radiograph (DRR), Anatomy Reconstruction, Statistical Shape and Intensity Model (SSIM), GPU acceleration Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-16580 SN - 1438-0064 ER - TY - JOUR A1 - Glatzeder, Korbinian A1 - Komnik, Igor A1 - Ambellan, Felix A1 - Zachow, Stefan A1 - Potthast, Wolfgang T1 - Dynamic pressure analysis of novel interpositional knee spacer implants in 3D-printed human knee models JF - Scientific Reports N2 - Alternative treatment methods for knee osteoarthritis (OA) are in demand, to delay the young (< 50 Years) patient’s need for osteotomy or knee replacement. Novel interpositional knee spacers shape based on statistical shape model (SSM) approach and made of polyurethane (PU) were developed to present a minimally invasive method to treat medial OA in the knee. The implant should be supposed to reduce peak strains and pain, restore the stability of the knee, correct the malalignment of a varus knee and improve joint function and gait. Firstly, the spacers were tested in artificial knee models. It is assumed that by application of a spacer, a significant reduction in stress values and a significant increase in the contact area in the medial compartment of the knee will be registered. Biomechanical analysis of the effect of novel interpositional knee spacer implants on pressure distribution in 3D-printed knee model replicas: the primary purpose was the medial joint contact stress-related biomechanics. A secondary purpose was a better understanding of medial/lateral redistribution of joint loading. Six 3D printed knee models were reproduced from cadaveric leg computed tomography. Each of four spacer implants was tested in each knee geometry under realistic arthrokinematic dynamic loading conditions, to examine the pressure distribution in the knee joint. All spacers showed reduced mean stress values by 84–88% and peak stress values by 524–704% in the medial knee joint compartment compared to the non-spacer test condition. The contact area was enlarged by 462–627% as a result of the inserted spacers. Concerning the appreciable contact stress reduction and enlargement of the contact area in the medial knee joint compartment, the premises are in place for testing the implants directly on human knee cadavers to gain further insights into a possible tool for treating medial knee osteoarthritis. Y1 - 2022 U6 - https://doi.org/10.1038/s41598-022-20463-6 VL - 12 ER -