Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives
Article
Raghavendra, U., Gudigar, Anjan, Paul, Aritra, Goutham, T.S., Inamdar, Mahesh Anil, Hegde, Ajay, Dev, Aruna, Ooi, Chui Ping, Deo, Ravinesh C., Barua, Prabal Datta, Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra. 2023. "Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives." Computers in Biology and Medicine. 163. https://doi.org/10.1016/j.compbiomed.2023.107063
Article Title | Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives |
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ERA Journal ID | 5040 |
Article Category | Article |
Authors | Raghavendra, U., Gudigar, Anjan, Paul, Aritra, Goutham, T.S., Inamdar, Mahesh Anil, Hegde, Ajay, Dev, Aruna, Ooi, Chui Ping, Deo, Ravinesh C., Barua, Prabal Datta, Molinari, Filippo, Ciaccio, Edward J. and Acharya, U. Rajendra |
Journal Title | Computers in Biology and Medicine |
Journal Citation | 163 |
Article Number | 107063 |
Number of Pages | 16 |
Year | 2023 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0010-4825 |
1879-0534 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.compbiomed.2023.107063 |
Web Address (URL) | https://www.sciencedirect.com/science/article/abs/pii/S0010482523005280 |
Abstract | A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting pressure on the healthy parts of the brain, it can lead to significant health problems. Depending on the region of the brain tumor, it can cause a wide range of health issues. As malignant brain tumors grow rapidly, the mortality rate of individuals with this cancer can increase substantially with each passing week. Hence it is vital to detect these tumors early so that preventive measures can be taken at the initial stages. Computer-aided diagnostic (CAD) systems, in coordination with artificial intelligence (AI) techniques, have a vital role in the early detection of this disorder. In this review, we studied 124 research articles published from 2000 to 2022. Here, the challenges faced by CAD systems based on different modalities are highlighted along with the current requirements of this domain and future prospects in this area of research. |
Keywords | Brain tumor; CT; Deep learning ; Machine learning ; MRI; Classification; PET; Segmentation |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Manipal Academy of Higher Education, India |
Consultant Neurosurgeon Manipal Hospitals, India | |
University of the Sunshine Coast | |
Singapore University of Social Sciences (SUSS), Singapore | |
School of Mathematics, Physics and Computing | |
School of Business | |
Cogninet Australia, Australia | |
University of Technology Sydney | |
Polytechnic University of Turin, Italy | |
Columbia University Irving Medical Center, United States | |
Kumamoto University, Japan |
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