Test-retest reproducibility of a multi-atlas automated segmentation tool on multimodality brain MRI.

ABSTRACT:

Introduction

The increasing use of large sample sizes for population and personalized medicine requires high-throughput tools for imaging processing that can handle large amounts of data with diverse image modalities, perform a biologically meaningful information reduction, and result in comprehensive quantification. Exploring the reproducibility of these tools reveals the specific strengths and weaknesses that heavily influence the interpretation of results, contributing to transparence in science.

Methods

We tested-retested the reproducibility of MRICloud, a free automated method for whole-brain, multimodal MRI segmentation and quantification, on two public, independent datasets of healthy adults.

Results

The reproducibility was extremely high for T1-volumetric anal

SUBMITTER: Rezende TJR 

PROVIDER: S-EPMC6790328 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature