Techniques for Detection and Analysis of Tumours from Brain MRI Images: A Review

  • Saurabh A Shah Babaria Institute of Technology, Gujarat Technological University
  • N C Chauhan Department of Information Technology, A D Patel Institute of Technology, Anand, Gujarat, India.
Keywords: tumour segmentation, medical image analysis, feature extraction, classification

Abstract

Analysis of MRI images and extraction of brain tumours from MRI images are challenging tasks in medical image processing. Researchers have contributed in segmenting and analysing brain tumour by applying varieties of the techniques and different hybrid approaches, however, due to diversity in appearance of tumour from patient to patient and also due to different tumour types, it has still been a challenge to exactly and correctly identify tumours from brain MRI image. Analysing brain MR images manually for finding exact boundaries of tumour by physicians is very time consuming and challenging due to low contrast MRI image and similarities of intensities between brain tissues. Many semi-automated and automated approaches have been developed to analyse MRI images and to delineate desired regions, such as tissues and tumour, and analyse their properties. This paper presents a comprehensive review of the state of the art methods for analysis of MRI images and methods for detection tumour from it. The review focuses, specifically, on important phases of MRI image analysis like feature extraction, segmentation and classification techniques. The challenges while processing brain MRI images as well as merits and demerits of existing methods for tumour analysis have been discussed.

Author Biography

Saurabh A Shah, Babaria Institute of Technology, Gujarat Technological University
Associate Professor, Department of Computer Science and Engineering

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Published
2016-03-03
How to Cite
Shah, S. A., & Chauhan, N. C. (2016). Techniques for Detection and Analysis of Tumours from Brain MRI Images: A Review. Journal of Biomedical Engineering and Medical Imaging, 3(1), 09. https://doi.org/10.14738/jbemi.31.1696