Automated detection and screening of traumatic brain injury (Tbi) using computed tomography images: A comprehensive review and future perspectives
Article
Vidhya, V., Gudigar, Anjan, Raghavendra, U., Hegde, Ajay, Menon, Girish R., Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra. 2021. "Automated detection and screening of traumatic brain injury (Tbi) using computed tomography images: A comprehensive review and future perspectives." International Journal of Environmental Research and Public Health. 18 (12). https://doi.org/10.3390/ijerph18126499
Article Title | Automated detection and screening of traumatic brain injury (Tbi) using computed tomography images: A comprehensive review and future perspectives |
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ERA Journal ID | 44293 |
Article Category | Article |
Authors | Vidhya, V., Gudigar, Anjan, Raghavendra, U., Hegde, Ajay, Menon, Girish R., Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra |
Journal Title | International Journal of Environmental Research and Public Health |
Journal Citation | 18 (12) |
Article Number | 6499 |
Number of Pages | 29 |
Year | 2021 |
Publisher | MDPI AG |
Place of Publication | Switzerland |
ISSN | 1660-4601 |
1661-7827 | |
Digital Object Identifier (DOI) | https://doi.org/10.3390/ijerph18126499 |
Web Address (URL) | https://www.mdpi.com/1660-4601/18/12/6499 |
Abstract | Traumatic brain injury (TBI) occurs due to the disruption in the normal functioning of the brain by sudden external forces. The primary and secondary injuries due to TBI include intracranial hematoma (ICH), raised intracranial pressure (ICP), and midline shift (MLS), which can result in significant lifetime disabilities and death. Hence, early diagnosis of TBI is crucial to improve patient outcome. Computed tomography (CT) is the preferred modality of choice to assess the severity of TBI. However, manual visualization and inspection of hematoma and its complications from CT scans is a highly operator-dependent and time-consuming task, which can lead to an inappropriate or delayed prognosis. The development of computer aided diagnosis (CAD) systems could be helpful for accurate, early management of TBI. In this paper, a systematic review of prevailing CAD systems for the detection of hematoma, raised ICP, and MLS in non-contrast axial CT brain images is presented. We also suggest future research to enhance the performance of CAD for early and accurate TBI diagnosis. |
Keywords | CAD; traumatic brain injury (TBI); computed tomography; intracranial hematoma; elevated ICP; midline shift |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Byline Affiliations | Manipal Academy of Higher Education, India |
Institute of Neurological Sciences, United Kingdom | |
Polytechnic University of Turin, Italy | |
Columbia University, United States | |
Singapore University of Social Sciences (SUSS), Singapore | |
Ngee Ann Polytechnic, Singapore | |
Asia University, Taiwan |
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https://research.usq.edu.au/item/z1w43/automated-detection-and-screening-of-traumatic-brain-injury-tbi-using-computed-tomography-images-a-comprehensive-review-and-future-perspectives
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