A Review on Computer Aided Diagnosis of Acute Brain Stroke

被引：34

作者：

Inamdar, Mahesh Anil ^{[1
]}

Raghavendra, Udupi ^{[2
]}

Gudigar, Anjan ^{[2
]}

Chakole, Yashas ^{[2
]}

Hegde, Ajay ^{[3
]}

Menon, Girish R. ^{[3
]}

Barua, Prabal ^{[4
,5
,6
]}

Palmer, Elizabeth Emma ^{[7
]}

Cheong, Kang Hao ^{[8
]}

Chan, Wai Yee ^{[9
]}

Ciaccio, Edward J. ^{[10
]}

Acharya, U. Rajendra ^{[11
,12
,13
,14
]}

机构：

[1] Manipal Acad Higher Educ, Manipal Inst Technol, Dept Mechatron, Manipal 576104, India

[2] Manipal Acad Higher Educ, Manipal Inst Technol, Dept Instrumentat & Control Engn, Manipal 576104, India

[3] Manipal Acad Higher Educ, Kasturba Med Coll, Dept Neurosurg, Manipal 576104, India

[4] Univ Southern Queensland, Sch Management & Enterprise, Toowoomba, Qld 4350, Australia

[5] Univ Technol, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia

[6] Cogninet Australia, Cogninet Brain Team, Sydney, NSW 2010, Australia

[7] Univ New South Wales, Sch Womens & Childrens Hlth, Sydney, NSW 2052, Australia

[8] Singapore Univ Technol & Design, Sci Math & Technol Cluster, Singapore 487372, Singapore

[9] Univ Malaya, Res Imaging Ctr, Dept Biomed Imaging, Kuala Lumpur 59100, Malaysia

[10] Columbia Univ, Dept Med, New York, NY 10032 USA

[11] Univ Malaya, Fac Engn, Dept Biomed Engn, Kuala Lumpur 50603, Malaysia

[12] Ngee Ann Polytech, Sch Engn, Singapore 599489, Singapore

[13] SUSS Univ, Sch Sci & Technol, Dept Biomed Engn, Singapore 599491, Singapore

[14] Asia Univ, Dept Biomed Informat & Med Engn, Taichung 41354, Taiwan

来源：

SENSORS | 2021年 / 21卷 / 24期

基金：

英国科研创新办公室;

关键词：

Ischemic brain stroke; machine learning; deep learning; CAD; ISCHEMIC-STROKE; LESION SEGMENTATION; SALVAGEABLE TISSUE; HEMORRHAGIC STROKE; GLOBAL BURDEN; CT PERFUSION; MRI; TOMOGRAPHY; PREDICTION; CLASSIFICATION;

D O I：

10.3390/s21248507

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Amongst the most common causes of death globally, stroke is one of top three affecting over 100 million people worldwide annually. There are two classes of stroke, namely ischemic stroke (due to impairment of blood supply, accounting for ~70% of all strokes) and hemorrhagic stroke (due to bleeding), both of which can result, if untreated, in permanently damaged brain tissue. The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke management. Abiding to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, we have surveyed a total of 177 research papers published between 2010 and 2021 to highlight the current status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation. This work concludes by showcasing the current requirement of this domain, the preferred modality, and prospective research areas.

引用

页数：35

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