Computer Assisted Unsupervised Extraction and Validation Technique for Brain Images from MRI

Title

Computer Assisted Unsupervised Extraction and Validation Technique for Brain Images from MRI

Creator

Vijayalakshmi S.; Genish T.; Gayathri S.P.

Description

Magnetic Resonance Imaging (MRI) of human is a developing field in medical research because it assists in considering the brain anomalies. To identify and analyze brain anomalies, the research requires brain extraction. Brain extraction is a significant clinical image handling method for quick conclusion with clinical perception for quantitative assessment. Automated methods of extracting brain from MRI are challenging, due to the connected pixel intensity information for various regions such as skull, sub head and neck tissues. This paper presents a fully automated extraction of brain area from MRI. The steps involved in developing the method to extract brain area, includes image contrast limited using histogram, background suppression using average filtering, pixel region growing method by finding pixel intensity similarity and filling discontinuity inside brain region. Twenty volumes of brain slices are utilized in this research method. The outcome is achieved by this method is approved by comparing with manually extracted slices. The test results confirm the performance of this strategy can effectively section brain from MRI. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-462, pp. 365-372.

Date

2022-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Brain anomalies; Brain extraction; Contrast limited; average filtering; Pixel intensity

Coverage

Vijayalakshmi S., Department of Data Science, ChristDeemed to be University, Pune, India; Genish T., School of Computing Science, KPR College of Arts Science and Research, Coimbatore, India; Gayathri S.P., Department of Computer Science and Applications, The Gandhigram Rural InstituteDeemed to be University, Gandhigram, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981192210-7

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-2211-4_32

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135062131&doi=10.1007%2f978-981-19-2211-4_32&partnerID=40&md5=b1273dd6d7b395a33955223cde21517a