Title: Brain cancer analysis using deep learning architecture on MRI brain image

Authors: B. Kannan; S. Karthigai Lakshmi

Addresses: Department of Electronics and Communication Engineering, Ramco Institute of Technology, Rajapalayam, India ' Department of Electronics and Communication Engineering, SSM Institute of Engineering and Technology, Dindigul, India

Abstract: Brain cancer diagnosis in the medical images sector without human involvement is a huge complex one. The brain tumour tissue can be detected from the whole brain are extremely difficult. Multi-sequence MRI technology is not standardised in brain tumour segmentation clinical practice and hence, a flexible segmentation process is required which uses all of the available MRI data optimally. The proposed algorithm provides a precise and robust segmentation of tumours, which helps in diagnosis, therapy planning, and risk factor detection. SVM classification and convolutional neural network classification are applied and analysed. The proposed system obtains more accurate predictions.

Keywords: image processing; MRI images; brain tumour; SVM classification; watershed image segmentation techniques; deep learning.

DOI: 10.1504/IJMEI.2024.139888

International Journal of Medical Engineering and Informatics, 2024 Vol.16 No.4, pp.363 - 373

Received: 06 Sep 2021
Accepted: 08 Feb 2022
Published online: 09 Jul 2024 *

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