Stroke Lesion Segmentation and Deep Learning: A Comprehensive Review

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aut.relation.issue1
aut.relation.journalBioengineering (Basel)
aut.relation.startpage86
aut.relation.volume11
dc.contributor.authorMalik, Mishaim
dc.contributor.authorChong, Benjamin
dc.contributor.authorFernandez, Justin
dc.contributor.authorShim, Vickie
dc.contributor.authorKasabov, Nikola Kirilov
dc.contributor.authorWang, Alan
dc.date.accessioned2024-02-01T03:43:29Z
dc.date.available2024-02-01T03:43:29Z
dc.date.issued2024-01-17
dc.description.abstractStroke is a medical condition that affects around 15 million people annually. Patients and their families can face severe financial and emotional challenges as it can cause motor, speech, cognitive, and emotional impairments. Stroke lesion segmentation identifies the stroke lesion visually while providing useful anatomical information. Though different computer-aided software are available for manual segmentation, state-of-the-art deep learning makes the job much easier. This review paper explores the different deep-learning-based lesion segmentation models and the impact of different pre-processing techniques on their performance. It aims to provide a comprehensive overview of the state-of-the-art models and aims to guide future research and contribute to the development of more robust and effective stroke lesion segmentation models.
dc.identifier.citationBioengineering (Basel), ISSN: 2306-5354 (Print); 2306-5354 (Online), MDPI AG, 11(1), 86-. doi: 10.3390/bioengineering11010086
dc.identifier.doi10.3390/bioengineering11010086
dc.identifier.issn2306-5354
dc.identifier.issn2306-5354
dc.identifier.urihttp://hdl.handle.net/10292/17177
dc.languageeng
dc.publisherMDPI AG
dc.relation.urihttps://www.mdpi.com/2306-5354/11/1/86
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectdeep learning
dc.subjectlesion segmentation
dc.subjectnetwork
dc.subjectstroke
dc.subjectdeep learning
dc.subjectlesion segmentation
dc.subjectnetwork
dc.subjectstroke
dc.subject40 Engineering
dc.subject4003 Biomedical Engineering
dc.subjectBehavioral and Social Science
dc.subjectNetworking and Information Technology R&D (NITRD)
dc.subjectNeurosciences
dc.subjectStroke
dc.subjectBrain Disorders
dc.subjectRehabilitation
dc.subjectStroke
dc.subject4003 Biomedical engineering
dc.titleStroke Lesion Segmentation and Deep Learning: A Comprehensive Review
dc.typeJournal Article
pubs.elements-id536589
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