A Neural Network Approach to Identify Left-Right Orientation of Anatomical Brain MRI.

ABSTRACT:

Purpose

This study presents a novel application of deep learning to enhance the accuracy of left-right orientation identification in anatomical brain MRI scans. Left-right orientation misidentification in brain MRIs presents significant challenges due to several factors, including metadata loss or ambiguity, which often occurs during the de-identification of medical images for research, conversion between image formats, software operations that strip or overwrite metadata, and the use of older imaging systems that stored orientation differently.

Method

A three-dimensional convolutional neural network model was trained using 350 MRIs and evaluated on the basis of eight distinct brain MRI databases, totaling 3056 MRIs, to assess its performance across various conditions, inclu

SUBMITTER: Nishimaki K 

PROVIDER: S-EPMC11808181 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature