Segmentation of large renal tumors in CT images by the integration of deep neural networks and thresholding

Abstract

To segment the kidney and its large tumors, we combine a deep neural network and thresholding technique. The deep network segments kidney, and its output is used to detect probable renal tumors. We compare the kidney volume with a normal kidney shape. Incomplete shapes are searched for tumors. Using a seed point the center of the tumor cluster is defined. Then, the pixels of a slice is labeled as normal or abnormal. The labeled pixels are post-processed using morphological filters to refine the result. The outcome of the algorithm is the tumor volume.