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Abstract
The process of segmenting tumor from MRI image of a brain is one of the highly focused
areas in the community of medical science as MRI is noninvasive imaging. This paper
discusses a thorough literature review of recent methods of brain tumor segmentation
from brain MRI images. It includes the performance and quantitative analysis of state-of-the-art
methods. Different methods of image segmentation are briefly explained with the recent
contribution of various researchers. Here, an effort is made to open new dimensions
for readers to explore the concerned area of research. Through the entire review process,
it has been observed that the combination of Conditional Random Field (CRF) with Fully
Convolutional Neural Network (FCNN) and CRF with DeepMedic or Ensemble are more effective
for the segmentation of tumor from the brain MRI images.