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Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives.
Raghavendra, U; Gudigar, Anjan; Paul, Aritra; Goutham, T S; Inamdar, Mahesh Anil; Hegde, Ajay; Devi, Aruna; Ooi, Chui Ping; Deo, Ravinesh C; Barua, Prabal Datta; Molinari, Filippo; Ciaccio, Edward J; Acharya, U Rajendra.
Afiliação
  • Raghavendra U; Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
  • Gudigar A; Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India. Electronic address: anjan.gudigar@manipal.edu.
  • Paul A; Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
  • Goutham TS; Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
  • Inamdar MA; Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
  • Hegde A; Consultant Neurosurgeon Manipal Hospitals, Sarjapur Road, Bangalore, India.
  • Devi A; School of Education and Tertiary Access, University of the Sunshine Coast, Caboolture Campus, Australia.
  • Ooi CP; School of Science and Technology, Singapore University of Social Sciences, Singapore, 599494, Singapore.
  • Deo RC; School of Mathematics, Physics, and Computing, University of Southern Queensland, Springfield, QLD, 4300, Australia.
  • Barua PD; 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 Techno
  • Molinari F; Department of Electronics and Telecommunications, Politecnico di Torino, 10129, Torino, Italy.
  • Ciaccio EJ; Department of Medicine, Columbia University Medical Center, New York, NY, 10032, USA.
  • Acharya UR; 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.
Comput Biol Med ; 163: 107063, 2023 09.
Article em En | MEDLINE | ID: mdl-37329621
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Inteligência Artificial Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Inteligência Artificial Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article