Automated segmentation of computed tomography colonography images using a 3D U-Net

PURPOSE: The segmentation of Computed Tomography (CT) colonography images is important to both colorectal research and diagnosis. This process often relies on manual interaction, and therefore depends on the user. Consequently, there is unavoidable interrater variability. An accurate method which eliminates this variability would be preferable. Current barriers to automated segmentation include discontinuities of the colon, liquid pooling, and...