Automated Segmentation of Kidney Cortex and Medulla in CT Images: A Multisite Evaluation Study.

ABSTRACT:

Background

In kidney transplantation, a contrast CT scan is obtained in the donor candidate to detect subclinical pathology in the kidney. Recent work from the Aging Kidney Anatomy study has characterized kidney, cortex, and medulla volumes using a manual image-processing tool. However, this technique is time consuming and impractical for clinical care, and thus, these measurements are not obtained during donor evaluations. This study proposes a fully automated segmentation approach for measuring kidney, cortex, and medulla volumes.

Methods

A total of 1930 contrast-enhanced CT exams with reference standard manual segmentations from one institution were used to develop the algorithm. A convolutional neural network model was trained (n=1238) and validated (n=306)

SUBMITTER: Korfiatis P 

PROVIDER: S-EPMC8819990 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature