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A Novel Technique to Detects and Segments Brain Tumor

P. Nagaveni1 , Chandra Mohan Reddy Sivappagari2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-7 , Page no. 1216-1219, Jul-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i7.12161219

Online published on Jul 31, 2018

Copyright © P. Nagaveni, Chandra Mohan Reddy Sivappagari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Nagaveni, Chandra Mohan Reddy Sivappagari, “A Novel Technique to Detects and Segments Brain Tumor,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.7, pp.1216-1219, 2018.

MLA Style Citation: P. Nagaveni, Chandra Mohan Reddy Sivappagari "A Novel Technique to Detects and Segments Brain Tumor." International Journal of Computer Sciences and Engineering 6.7 (2018): 1216-1219.

APA Style Citation: P. Nagaveni, Chandra Mohan Reddy Sivappagari, (2018). A Novel Technique to Detects and Segments Brain Tumor. International Journal of Computer Sciences and Engineering, 6(7), 1216-1219.

BibTex Style Citation:
@article{Nagaveni_2018,
author = {P. Nagaveni, Chandra Mohan Reddy Sivappagari},
title = {A Novel Technique to Detects and Segments Brain Tumor},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {6},
Issue = {7},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {1216-1219},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2586},
doi = {https://doi.org/10.26438/ijcse/v6i7.12161219}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i7.12161219}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2586
TI - A Novel Technique to Detects and Segments Brain Tumor
T2 - International Journal of Computer Sciences and Engineering
AU - P. Nagaveni, Chandra Mohan Reddy Sivappagari
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 1216-1219
IS - 7
VL - 6
SN - 2347-2693
ER -

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Abstract

The specialist area of medical imaging is gaining significance in the prevalent times due to the ever-increasing need of automated and speedy diagnosis in the shortest period of time. According to the literature available, researchers have suggested that clustering, Fuzzy K-C-Means (FCM), Magnetic Resonance Imaging (MRI), K-means methods are extremely effective for timely detection and segmentation of brain tumor with the help of MRI scanned images. Some of the major limitations of these methods include complexity, ambiguous nature of the fuzzy boundaries, and diversified nature of the infarct areas or regions. This paper proposes a new technique for overcoming these drawbacks or limitations by using Conditional Random Field (CRF) based framework. The suggested method combines the information in Tumor 1 (T1) and FLAIR in probabilistic domain, so that the foreground and back ground are identified. The performance of the proposed method is validated using peal signal to noise ratio, sensitivity, specificity, accuracy, Jacard coefficient and Dice coefficient. CRF based framework is an efficient and simple method that can be incorporated for modelling shapes and for observing the functions of energy.

Key-Words / Index Term

Brain Tumor, MRI Images, Fuzzy C-means clustering, Energy function, Conditional Random Field (CRF).

References

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