Bladder segmentation in MR images with watershed segmentation and graph cut algorithm

Thomas Blaffert; Steffen Renisch; Nicole Schadewaldt; Heinrich Schulz; Rafael Wiemker

doi:10.1117/12.2044049

21 March 2014 Bladder segmentation in MR images with watershed segmentation and graph cut algorithm

Thomas Blaffert, Steffen Renisch, Nicole Schadewaldt, Heinrich Schulz, Rafael Wiemker

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90344C (2014) https://doi.org/10.1117/12.2044049
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

Prostate and cervix cancer diagnosis and treatment planning that is based on MR images benefit from superior soft tissue contrast compared to CT images. For these images an automatic delineation of the prostate or cervix and the organs at risk such as the bladder is highly desirable. This paper describes a method for bladder segmentation that is based on a watershed transform on high image gradient values and gray value valleys together with the classification of watershed regions into bladder contents and tissue by a graph cut algorithm. The obtained results are superior if compared to a simple region-after-region classification.

Citation Download Citation

Thomas Blaffert, Steffen Renisch, Nicole Schadewaldt, Heinrich Schulz, and Rafael Wiemker "Bladder segmentation in MR images with watershed segmentation and graph cut algorithm", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90344C (21 March 2014); https://doi.org/10.1117/12.2044049

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