Inamdar, Mahesh Anil and Raghavendra, Udupi and Gudigar, Anjan and Chakole, Yashas and Hegde, Ajay and Menon, Girish R. and Barua, Prabal and Palmer, Elizabeth Emma and Cheong, Kang Hao and Chan, Wai Yee and Ciaccio, Edward J. and Acharya, U. Rajendra (2021) A review on computer aided diagnosis of acute brain stroke. Sensors, 21 (24). ISSN 1424-8220, DOI https://doi.org/10.3390/s21248507.
Full text not available from this repository.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
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Ischemic brain stroke;Machine learning;Deep learning;CAD |
| Subjects: | R Medicine R Medicine > R Medicine (General) > Medical technology R Medicine > RC Internal medicine R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 14 Sep 2022 07:37 |
| Last Modified: | 14 Sep 2022 07:37 |
| URI: | http://eprints.um.edu.my/id/eprint/34522 |
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