Gudigar, Anjan and Raghavendra, U and Hegde, Ajay and Kalyani, M and Ciaccio, Edward J and Acharya, Rajendra U (2020) Brain pathology identification using computer aided diagnostic tool: A systematic review. Computer Methods and Programs, 187. ISSN 0169-2607
![]() |
PDF
9071.pdf - Published Version Restricted to Registered users only Download (4MB) | Request a copy |
Abstract
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-of-life by reducing human errors in diagnosis. CAD can expedite decision-making on complex clinical data automatically. Since brain diseases can be fatal, rapid identification of brain pathology to prolong patient life is an important research topic. Many algorithms have been proposed for efficient brain pathology identification (BPI) over the past decade. Constant refinement of the various image processing algorithms must take place to expand performance of the automatic BPI task. In this paper, a systematic survey of contemporary BPI algorithms using brain magnetic resonance imaging (MRI) is presented. A summarization of recent literature provides investigators with a helpful synopsis of the domain. Furthermore, to enhance the performance of BPI, future research directions are indicated.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Brain pathology Computer aided diagnostic Classification Deep learning Feature extraction Magnetic resonance imaging |
Subjects: | Engineering > MIT Manipal > Instrumentation and Control |
Depositing User: | MIT Library |
Date Deposited: | 25 Sep 2020 07:04 |
Last Modified: | 25 Sep 2020 07:04 |
URI: | http://eprints.manipal.edu/id/eprint/155687 |
Actions (login required)
![]() |
View Item |