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

Authors
Nasiri, Nasim
Mohagheghi, Saeed
Hossein Foruzan, Amir

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

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.

Identifiers
doi: 10.24926/548719.093