Abstract
The purpose of this study was to evaluate m-rep deformable models for automatic segmentation of multi-object soft-tissue complexes in low contrast images with application to bladder, rectum and prostate in planning and treatment CT images. M-rep deformation is guided by knowledge of object and inter-object geometry and image intensity patterns gained through a statistical training procedure. The method is broadly applicable but is tested here for adaptive radiotherapy for prostate cancer, where the segmentation is applied to CT images acquired in the treatment room over the course of radiotherapy.
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