Rectifying Whole Brain Segmentation Errors Using a Novel Under-Segmentation Correction Method

Title

Rectifying Whole Brain Segmentation Errors Using a Novel Under-Segmentation Correction Method

Creator

Sujana, D. Swainson; Augustine, D. Peter

Description

Pre-processing is a critical step in any data-driven study, particularly in the field of medical imaging, where it significantly enhances the reliability of disease and disorder diagnosis. In this context, medical image segmentation allows for more precise data analysis by isolating the regions of interest. Accurate segmentation of these regions can reveal influential variabilities in analysis, potentially leading to unique scientific findings. This article presents a novel under-segmentation error correction technique specifically designed for whole-brain segmentation. Additionally, it performs a set of pre-processing steps for the structural magnetic resonance imaging (sMRI) images, which are necessary to maintain the structural integrity and uniformity of MRI scans across different subjects. The proposed algorithm effectively eliminates under-segmentation errors, thereby improving the accuracy of whole-brain segmentation, particularly for structurally intact brain images. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Source

Communications in Computer and Information Science;Volume;2461 CCIS;pp.418-427

Date

01-01-2025

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

pre-process; registration; skull stripping; smri; Under-segmentation

Coverage

Sujana D.S., Christ (Deemed to be University), Bangalore, India; Augustine D.P., Christ (Deemed to be University), Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 18650929; ISBN: 978-303196472-5;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-3-031-96473-2_30

https://www.scopus.com/pages/publications/105010833118?origin=resultslist