• Publications
  • Influence
Evaluation of segmentation methods on head and neck CT: Auto‐segmentation challenge 2015
Purpose Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms,Expand
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Segmentation of vessels: the corkscrew algorithm
Medical imaging is nowadays much more than only providing data for diagnosis. It also links 'classical' diagnosis to modern forms of treatment such as image guided surgery. Those systems require theExpand
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VR-Based Simulators for Training in Minimally Invasive Surgery
Simulation-based training using VR techniques is a promising alternative to traditional training in minimally invasive surgery (MIS). Simulators let the trainee touch, feel, and manipulate virtualExpand
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Automatic Prostate Segmentation in MR Images with a Probabilistic Active Shape Model
Segmentation of the prostate gland in Magnetic Resonance (MR) images is an important task for image-guided prostate cancer therapy. The low contrast of the prostate to surrounding tissue in MR imagesExpand
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Localizing Calcifications in Cardiac CT Data Sets Using a New Vessel Segmentation Approach
The new generation of multislice computed tomography (CT) scanners allows for the acquisition of high-resolution images of the heart. Based on that image data, the heart can be analyzed in aExpand
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3D Active Shape Model Segmentation with Nonlinear Shape Priors
The Active Shape Model (ASM) is a segmentation algorithm which uses a Statistical Shape Model (SSM) to constrain segmentations to 'plausible' shapes. This makes it possible to robustly segment organsExpand
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Opening up the “black box” of medical image segmentation with statistical shape models
The importance of medical image segmentation increases in fields like treatment planning or computer aided diagnosis. For high quality automatic segmentations, algorithms based on statistical shapeExpand
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Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the small bowel. So farExpand
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Automated Kidney Detection and Segmentation in 3D Ultrasound
Ultrasound provides the physical capabilities for a fast and save disease diagnosis in various medical scenarios including renal exams and patient trauma assessment. However, the experience of theExpand
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Combining short-axis and long-axis cardiac MR images by applying a super-resolution reconstruction algorithm
In cardiac MR images the slice thickness is normally greater than the pixel size within the slices. In general, better segmentation and analysis results can be expected for isotropic high-resolutionExpand
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