Treatment of rectal cancer often requires repeated identification of the tumor volume by means of manual delineation by expert radiologists or oncologists. This is a tedious and time-consuming task, particularly with the growing use of multi-sequence 3D imaging. In this work, we have implemented a deep neural network for automatic detection and segmentation of rectal cancer. Our model demonstrates high detection and segmentation performance, equivalent to that of an expert reader, thus illustrating the potential use of deep learning-based segmentation in a clinically relevant setting.
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