Age-related morphometrics of normal adrenal glands based on deep learning-aided segmentation.

ABSTRACT:

Objective

This study aims to evaluate the morphometrics of normal adrenal glands in adult patients semiautomatically using a deep learning-based segmentation model.

Materials and methods

A total of 520 abdominal CT image series with normal findings, from January 1, 2016, to March 14, 2019, were retrospectively collected for the training of the adrenal segmentation model. Then, 1043 portal venous phase image series of inpatient contrast-enhanced abdominal CT examinations with normal adrenal glands were included for analysis and grouped by every 10-year gap. A 3D U-Net-based segmentation model was used to predict bilateral adrenal labels followed by manual modification of labels as appropriate. Quantitative parameters (volume, CT value, and diameters) of the bilateral adrenal

SUBMITTER: Chen Y 

PROVIDER: S-EPMC10279821 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature