Preliminary study on the application of renal ultrasonography radiomics in the classification of glomerulopathy.

ABSTRACT:

Background

The aim of this study was to investigate the potential use of renal ultrasonography radiomics features in the histologic classification of glomerulopathy.

Methods

A total of 623 renal ultrasound images from 46 membranous nephropathy (MN) and 22 IgA nephropathy patients were collected. The cases and images were divided into a training group (51 cases with 470 images) and a test group (17 cases with 153 images). A total of 180 dimensional features were designed and extracted from the renal parenchyma in the ultrasound images. Least absolute shrinkage and selection operator (LASSO) logistic regression was then applied to these normalized radiomics features to select the features with the highest correlations. Four machine learning classifiers, including logistic regr

SUBMITTER: Zhang L 

PROVIDER: S-EPMC8305820 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature