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Sensors
Volume 21
Issue 24
10.3390/s21248507
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Review

A Review on Computer Aided Diagnosis of Acute Brain Stroke

by
Mahesh Anil Inamdar
1,
Udupi Raghavendra
2,*,
Anjan Gudigar
2,
Yashas Chakole
2,
Ajay Hegde
3,
Girish R. Menon
3,
Prabal Barua
4,5,6,
Elizabeth Emma Palmer
7,
Kang Hao Cheong
8,
Wai Yee Chan
9,
Edward J. Ciaccio
10 and
U. Rajendra Acharya
11,12,13,14
1
Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India
2
Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India
3
Department of Neurosurgery, Kasturba Medical College, Manipal Academy of Higher Education, Manipal 576104, India
4
School of Management & Enterprise, University of Southern Queensland, Toowoomba, QLD 4350, Australia
5
Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia
6
Cogninet Brain Team, Cogninet Australia, Sydney, NSW 2010, Australia
7
School of Women’s and Children’s Health, University of New South Wales, Sydney, NSW 2052, Australia
8
Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, Singapore 487372, Singapore
9
Department of Biomedical Imaging, Research Imaging Centre, University of Malaya, Kuala Lumpur 59100, Malaysia
10
Department of Medicine, Columbia University, New York, NY 10032, USA
11
Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
12
School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore
13
Department of Biomedical Engineering, School of Science and Technology, SUSS University, Singapore 599491, Singapore
14
Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
 
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*
Author to whom correspondence should be addressed.
Sensors 2021, 21(24), 8507; https://doi.org/10.3390/s21248507
Submission received: 4 October 2021 / Revised: 5 December 2021 / Accepted: 9 December 2021 / Published: 20 December 2021
(This article belongs to the Special Issue Innovations in Biomedical Imaging)
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Abstract

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.
Keywords: Ischemic brain stroke; machine learning; deep learning; CAD Ischemic brain stroke; machine learning; deep learning; CAD

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MDPI and ACS Style

Inamdar, M.A.; Raghavendra, U.; Gudigar, A.; Chakole, Y.; Hegde, A.; Menon, G.R.; Barua, P.; Palmer, E.E.; Cheong, K.H.; Chan, W.Y.; et al. A Review on Computer Aided Diagnosis of Acute Brain Stroke. Sensors 2021, 21, 8507. https://doi.org/10.3390/s21248507

AMA Style

Inamdar MA, Raghavendra U, Gudigar A, Chakole Y, Hegde A, Menon GR, Barua P, Palmer EE, Cheong KH, Chan WY, et al. A Review on Computer Aided Diagnosis of Acute Brain Stroke. Sensors. 2021; 21(24):8507. https://doi.org/10.3390/s21248507

Chicago/Turabian Style

Inamdar, Mahesh Anil, Udupi Raghavendra, Anjan Gudigar, Yashas Chakole, Ajay Hegde, Girish R. Menon, Prabal Barua, Elizabeth Emma Palmer, Kang Hao Cheong, Wai Yee Chan, and et al. 2021. "A Review on Computer Aided Diagnosis of Acute Brain Stroke" Sensors 21, no. 24: 8507. https://doi.org/10.3390/s21248507

APA Style

Inamdar, M. A., Raghavendra, U., Gudigar, A., Chakole, Y., Hegde, A., Menon, G. R., Barua, P., Palmer, E. E., Cheong, K. H., Chan, W. Y., Ciaccio, E. J., & Acharya, U. R. (2021). A Review on Computer Aided Diagnosis of Acute Brain Stroke. Sensors, 21(24), 8507. https://doi.org/10.3390/s21248507

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