Gloger, OliverEhrhardt, MatthiasDietrich, ThoreHellwich, OlafNagel, Eike2022-05-112022-05-112007-09-102197-8085https://depositonce.tu-berlin.de/handle/11303/16880http://dx.doi.org/10.14279/depositonce-15658In this work we propose an adapted level set segmentation technique for the recognition of atherosclerotic plaque tissue on magnetic resonance images. The segmentation technique is subdivided into three steps whereas the result of every phase serves as additional prior knowledge for the next level set step. By incorporating special knowledge derived from the images into the level set equation we guide the level set towards the desired plaque patterns. By analyzing and applying carefully all disposable channel information we are capable to border the vessel walls on the images and after that approach an enclosing level set which circumvents the plaque patterns from healthy media tissue. We support the plaque detection with so-called canny edges and locally weighted intensity information for conspicuous plaque patterns. We justify the introduction of a maximal shrinking distance of the 3rd level set in the vessel wall for supporting segmentation and show very promising results of this method in special figures during the level set propagation. By extending the level set segmentation with our concepts of locally weighted intensity information and the maximal shrinking distance we teach the level sets to segment the dangerous plaque patterns very exactly. Furthermore we are capable to emphasize and segment plaque patterns which are difficult to recognize even for the human observer.en510 Mathematiklevel set segmentationactive contoursmedical image segmentationanisotropic diffusionatherosclerotic plaquescanny edgesResearch Paper