Effect of grey-level discretization on texture feature on different weighted MRI images of diverse disease groups.

ABSTRACT:

Purpose

Many studies of MRI radiomics do not include the discretization method used for the analyses, which might indicate that the discretization methods used are considered irrelevant. Our goals were to compare three frequently used discretization methods (lesion relative resampling (LRR), lesion absolute resampling (LAR) and absolute resampling (AR)) applied to the same data set, along with two different lesion segmentation approaches.

Methods

We analyzed the effects of altering bin widths or bin numbers for the three different sampling methods using 40 texture indices (TIs). The impact was evaluated on brain MRI studies obtained for 71 patients divided into three different disease groups: multiple sclerosis (MS, N = 22), ischemic stroke (IS, N = 22), cancer patients (N =

SUBMITTER: Veres G 

PROVIDER: S-EPMC8213143 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature