Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives

U Raghavendra; Anjan Gudigar; Aritra Paul; T S Goutham; Mahesh Anil Inamdar; Ajay Hegde; Aruna Devi; Chui Ping Ooi; Ravinesh C Deo; Prabal Datta Barua; Filippo Molinari; Edward J Ciaccio; U Rajendra Acharya

doi:10.1016/j.compbiomed.2023.107063

Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives

Comput Biol Med. 2023 Sep:163:107063. doi: 10.1016/j.compbiomed.2023.107063. Epub 2023 Jun 1.

Authors

Affiliations

¹ Department of Instrumentation and Control Engineering, 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. Electronic address: anjan.gudigar@manipal.edu.
³ Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
⁴ Consultant Neurosurgeon Manipal Hospitals, Sarjapur Road, Bangalore, India.
⁵ School of Education and Tertiary Access, University of the Sunshine Coast, Caboolture Campus, Australia.
⁶ School of Science and Technology, Singapore University of Social Sciences, Singapore, 599494, Singapore.
⁷ School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, QLD, 4300, Australia.
⁸ Cogninet Brain Team, Cogninet Australia, Sydney, NSW, 2010, Australia; School of Business (Information Systems), Faculty of Business, Education, Law & Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia; Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, 2007, Australia.
⁹ Department of Electronics and Telecommunications, Politecnico di Torino, 10129, Torino, Italy.
¹⁰ Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA.
¹¹ School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, QLD, 4300, Australia; International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, 860-8555, Japan.

PMID: 37329621
DOI: 10.1016/j.compbiomed.2023.107063

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; Classification; Deep learning; MRI; Machine learning; PET; Segmentation.

Publication types

Review

MeSH terms

Artificial Intelligence*
Brain
Brain Neoplasms* / diagnosis
Humans
Radiopharmaceuticals
Skull

Substances

Radiopharmaceuticals