Patch-based renal CTA image segmentation with U-Net

This article presents an innovative processing method of computed tomography image-slices for automatic identification of kidneys and cancers boundaries. The system was developed based on the use of U-Net convolutional neural network. The innovative solution proposed in the presented experiments uses the technique of automatically partitioning the input data into frames of fixed dimensions, containing only areas of interest. The developed technique allows obtaining accurate boundaries of the kidneys and cancers with high accuracy, comparable to a human expert. The obtained segmentation accuracy is satisfactory and equals 96 % for renal, 74% for renal cell cancers and 90 % for cystics.