TY - GEN A1 - Lamas-Rodríguez, Julián A1 - Ehlke, Moritz A1 - Hoffmann, René A1 - Zachow, Stefan T1 - GPU-accelerated denoising of large tomographic data sets with low SNR BT - Application for non-invasive analysis of paleontological data N2 - Enhancements in tomographic imaging techniques facilitate non-destructive methods for visualizing fossil structures. However, to penetrate dense materials such as sediments or pyrites, image acquisition is typically performed with high beam energy and very sensitive image intensifiers, leading to artifacts and noise in the acquired data. The analysis of delicate fossil structures requires the images to be captured in maximum resolution, resulting in large data sets of several giga bytes (GB) in size. Since the structural information of interest is often almost in the same spatial range as artifacts and noise, image processing and segmentation algorithms have to cope with a very low signal-to-noise ratio (SNR). Within this report we present a study on the performance of a collection of denoising algorithms applied to a very noisy fossil dataset. The study shows that a non-local means (NLM) filter, in case it is properly configured, is able to remove a considerable amount of noise while preserving most of the structural information of interest. Based on the results of this study, we developed a software tool within ZIBAmira that denoises large tomographic datasets using an adaptive, GPU-accelerated NLM filter. With the help of our implementation a user can interactively configure the filter's parameters and thus its effectiveness with respect to the data of interest, while the filtering response is instantly visualized for a preselected region of interest (ROI). Our implementation efficiently denoises even large fossil datasets in a reasonable amount of time. T3 - ZIB-Report - 15-14 Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-56339 SN - 1438-0064 ER - TY - GEN A1 - Ehlke, Moritz A1 - Frenzel, Thomas A1 - Ramm, Heiko A1 - Shandiz, Mohsen Akbari A1 - Anglin, Carolyn A1 - Zachow, Stefan T1 - Towards Robust Measurement of Pelvic Parameters from AP Radiographs using Articulated 3D Models N2 - Patient-specific parameters such as the orientation of the acetabulum or pelvic tilt are useful for custom planning for total hip arthroplasty (THA) and for evaluating the outcome of surgical interventions. The gold standard in obtaining pelvic parameters is from three-dimensional (3D) computed tomography (CT) imaging. However, this adds time and cost, exposes the patient to a substantial radiation dose, and does not allow for imaging under load (e.g. while the patient is standing). If pelvic parameters could be reliably derived from the standard anteroposterior (AP) radiograph, preoperative planning would be more widespread, and research analyses could be applied to retrospective data, after a postoperative issue is discovered. The goal of this work is to enable robust measurement of two surgical parameters of interest: the tilt of the anterior pelvic plane (APP) and the orientation of the natural acetabulum. We present a computer-aided reconstruction method to determine the APP and natural acetabular orientation from a single, preoperative X-ray. It can easily be extended to obtain other important preoperative and postoperative parameters solely based on a single AP radiograph. T3 - ZIB-Report - 15-11 KW - Articulated Models, Statistical Shape And Intensity Models, 2D/3D Anatomy Reconstruction, Pelvic Parameters Measurement, Total Hip Arthroplasty Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-53707 SN - 1438-0064 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 - GEN A1 - Ehlke, Moritz A1 - Ramm, Heiko A1 - Lamecker, Hans A1 - Hege, Hans-Christian A1 - Zachow, Stefan T1 - Fast Generation of Virtual X-ray Images from Deformable Tetrahedral Meshes N2 - We propose a novel GPU-based approach to render virtual X-ray projections of deformable tetrahedral meshes. These meshes represent the shape and the internal density distribution of a particular anatomical structure and are derived from statistical shape and intensity models (SSIMs). We apply our method to improve the geometric reconstruction of 3D anatomy (e.g.\ pelvic bone) from 2D X-ray images. For that purpose, shape and density of a tetrahedral mesh are varied and virtual X-ray projections are generated within an optimization process until the similarity between the computed virtual X-ray and the respective anatomy depicted in a given clinical X-ray is maximized. The OpenGL implementation presented in this work deforms and projects tetrahedral meshes of high resolution (200.000+ tetrahedra) at interactive rates. It generates virtual X-rays that accurately depict the density distribution of an anatomy of interest. Compared to existing methods that accumulate X-ray attenuation in deformable meshes, our novel approach significantly boosts the deformation/projection performance. The proposed projection algorithm scales better with respect to mesh resolution and complexity of the density distribution, and the combined deformation and projection on the GPU scales better with respect to the number of deformation parameters. The gain in performance allows for a larger number of cycles in the optimization process. Consequently, it reduces the risk of being stuck in a local optimum. We believe that our approach contributes in orthopedic surgery, where 3D anatomy information needs to be extracted from 2D X-rays to support surgeons in better planning joint replacements. T3 - ZIB-Report - 13-38 KW - digitally reconstructed radiographs KW - volume rendering KW - mesh deformation KW - statistical shape and intensity models KW - image registration KW - GPU acceleration Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-41896 SN - 1438-0064 ER - TY - GEN A1 - Ehlke, Moritz A1 - Frenzel, Thomas A1 - Ramm, Heiko A1 - Lamecker, Hans A1 - Akbari Shandiz, Mohsen A1 - Anglin, Carolyn A1 - Zachow, Stefan T1 - Robust Measurement of Natural Acetabular Orientation from AP Radiographs using Articulated 3D Shape and Intensity Models T3 - ZIB-Report - 14-12 KW - articulated shape and intensity models KW - 3D reconstruction KW - acetabular orientation KW - image registration Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-49824 SN - 1438-0064 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 - 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 - GEN A1 - Ehlke, Moritz A1 - Heyland, Mark A1 - Märdian, Sven A1 - Duda, Georg A1 - Zachow, Stefan T1 - 3D Assessment of Osteosynthesis based on 2D Radiographs N2 - We present a novel method to derive the surface distance of an osteosynthesis plate w.r.t. the patient-specific surface of the distal femur based on postoperative 2D radiographs. In a first step, the implant geometry is used as a calibration object to relate the implant and the individual X-ray images spatially in a virtual X-ray setup. Second, the patient-specific femoral shape and pose are reconstructed by fitting a deformable statistical shape and intensity model (SSIM) to the X-rays. The relative positioning between femur and implant is then assessed in terms of the displacement between the reconstructed 3D shape of the femur and the plate. We believe that the approach presented in this paper constitutes a meaningful tool to elucidate the effect of implant positioning on fracture healing and, ultimately, to derive load recommendations after surgery. T3 - ZIB-Report - 15-47 KW - 3d-reconstruction from 2d X-rays KW - statistical shape and intensity models KW - osteosynthesis follow-up Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-56217 SN - 1438-0064 ER -