A Review of Brain Tumor Image Segmentation of MR Images Using Deep Learning Methods

Authors

Amishi Vijay
Dept. of Electronics and Communication, Dr. B.R. Ambedkar National Institute of Technology, Jalandhar
Jasleen Saini
Dept of CSE UIET, Panjab University Chandigarh, India
B.S. Saini
Department of ECE Dr. B.R. Ambedkar National Institute of Technology Jalandhar, India

Synopsis

A significant analysis is routine for Brain Tumor patients and it depends on accurate segmentation of Region of Interest. In automatic segmentation, field deep learning algorithms are attaining interest after they have performed very well in various ImageNet competitions. This review focuses on state-of-the-art Deep Learning Algorithms which are applied to Brain Tumor Segmentation. First, we review the methods of brain tumor segmentation, next the different deep learning algorithms and their performance measures like sensitivity, specificity and Dice similarity Coefficient (DSC) are discussed and Finally, we discuss and summarize the current deep learning techniques and identify future scope and trends.

WREC21
Published
September 22, 2021
Online ISSN
2582-3922