Development and verification of radiomics framework for computed tomography image segmentation.

ABSTRACT:

Background

Radiomics has been considered an imaging marker for capturing quantitative image information (QII). The introduction of radiomics to image segmentation is desirable but challenging.

Purpose

This study aims to develop and validate a radiomics-based framework for image segmentation (RFIS).

Methods

RFIS is designed using features extracted from volume (svfeatures) created by sliding window (swvolume). The 53 svfeatures are extracted from 11 phantom series. Outliers in the svfeature datasets are detected by isolation forest (iForest) and specified as the mean value. The percentage coefficient of variation (%COV) is calculated to evaluate the reproducibility of svfeatures. RFIS is constructed and applied to the gross target volume (GTV) segmentation from the per

SUBMITTER: Gu J 

PROVIDER: S-EPMC9805121 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature