A Review on Various Image Segmentation Techniques for Brain Tumor Detection

Authors(2) :-Munmun Saha, Chandrasekhar Panda

Segmentation is consider as one of the main step in image processing and it plays and important role in image processing. It is the process of subdividing an image into its constituent parts. In this paper we have reviewed various methods of segmentation and its application in medical image processing i.e. MRI image Ultrasound Image etc, we have focused on Brain Tumor MRI image. Recent medical imaging research faces the challenge of detecting brain tumor through MRI(Magnetic Resonance Image). There is a high diversity in the appearance of tumor tissue among different patients and in many cases similarity with the usual tissue. We have used MRI because it provide accurate visualize of anatomical structure of tissue. In this paper various method that have been used for segmentation of MRI for detecting brain tumor is reviewed.

Authors and Affiliations

Munmun Saha
Department of Computer Science and Application, Sambalpur University, Jyoti Vihar, Sambalpur, Odisha, India
Chandrasekhar Panda
Department of Computer Science and Application, Sambalpur University, Jyoti Vihar, Sambalpur, Odisha, India

MRI, Segmentation, Clustering, K-means algorithm, Fuzzy C-mean algorithm, edge detection, Thresholding, Region Growing, Region Splitting, Watershed Segmentation Algorithm, Entropy, SVM.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 21-30
Manuscript Number : CSEIT18317
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Munmun Saha, Chandrasekhar Panda , "A Review on Various Image Segmentation Techniques for Brain Tumor Detection", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.21-30, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT18317

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