Title: Feature extraction for brain tumour analysis and classification: a review

Authors: Rajat Mehrotra; M.A. Ansari

Addresses: Department of Electrical & Electronics Engineering, GL Bajaj Institute of Technology & Management, Greater Noida, India ' Department of Electrical Engineering, School of Engineering, Gautam Buddha University, Greater Noida, India

Abstract: The most vital organ of the human body is brain which organises the whole of the sensory system. The presented paper provides a knowledgeable perception of diverse strategies utilised by various researchers for segmentation and identification of brain tumour (BT) using distinct methods and approaches. Among various imaging modalities, MRI images are acknowledged here as an input of superior quality for the purpose of conducting research when compared to other existing modern practices for superior and more precise outcome. Biomedical image processing has witnessed exponential growth, and has been a multidisciplinary area of research attracting experts not only from medical field but from various other fields of engineering and sciences. Computer-aided diagnostic processing has already become an important part of clinical routine.

Keywords: magnetic resonance imaging; MRI; classification; segmentation; feature extraction; fuzzy C-means; FCMs; neuro fuzzy; genetic algorithm; GA; grey-level co-occurrence matrix; GLCM; histogram of oriented gradient; HoG; linear binary pattern; LBP; discrete wavelet transform; DWT.

DOI: 10.1504/IJDSSS.2020.106083

International Journal of Digital Signals and Smart Systems, 2020 Vol.4 No.1/2/3, pp.199 - 218

Received: 25 May 2019
Accepted: 31 May 2019
Published online: 27 Mar 2020 *