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A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method

R. Subhulakshmi1

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-08 , Page no. 38-43, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si8.3843

Online published on Apr 10, 2019

Copyright © R. Subhulakshmi . 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: R. Subhulakshmi, “A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.08, pp.38-43, 2019.

MLA Style Citation: R. Subhulakshmi "A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method." International Journal of Computer Sciences and Engineering 07.08 (2019): 38-43.

APA Style Citation: R. Subhulakshmi, (2019). A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method. International Journal of Computer Sciences and Engineering, 07(08), 38-43.

BibTex Style Citation:
@article{Subhulakshmi_2019,
author = {R. Subhulakshmi},
title = {A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {08},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {38-43},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=912},
doi = {https://doi.org/10.26438/ijcse/v7i8.3843}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.3843}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=912
TI - A Novel Segmentation Technique to Extract Amygalada of Brain to Detect Insomnia Disorder Using Graph Cut Method
T2 - International Journal of Computer Sciences and Engineering
AU - R. Subhulakshmi
PY - 2019
DA - 2019/04/10
PB - IJCSE, Indore, INDIA
SP - 38-43
IS - 08
VL - 07
SN - 2347-2693
ER -

           

Abstract

Insomnia is one of the most dangerous sleepless disorders and can continue through the teenage years and lifelong of human being. This research work focuses on one of the major problems of this disorder happen in human brain called amygalada abnormality. The size and growth of the amygalada will decide the insomnia disorder. Various existing research works to extract the amygalada (Head and body) are surveyed in this thesis and an automatic diagnosis technique is proposed to extract the amygalada in MRI brain images. In the proposed method, Graph Cut Method is used to make it suitable for segmenting small, low contrast structure such as the amygalada to predicting the Insomnia Disorder. The results show accurate and very fast performances in external amygalada segmentation in a real data set.

Key-Words / Index Term

Insomnia, Amygalada, Graph Cut, MRI, Segmentation

References

[1] http://www.optisom.com/introduction-to-insomnia/
[2] http://medical-dictionary.thefreedictionary.com/insomnia
[3] http://www.onlymyhealth.com/who-affected-insomnia-1316675052
[4] http://www.mayoclinic.org/diseases-conditions/insomnia/basics/causes/con-20024293
[5] Doan, H., Slabaugh, G.G., Unal, G.B. & Fang, T. (2006). Semi-Automatic 3-D Segmentation of Anatomical Structures of Brain MRI Volumes using Graph Cuts. Paper presented at the 2006 IEEE International Conference on Image Processing,, 08-10-2006 - 11-10-2006, Atlanta, USA.
[6] Igual L, Soliva JC, Gimeno AR, Escalera S, Vilarroya O, RadevaP: Automatic Internal Segmentation of Amygaladafor Diagnosis of Attention-Deficit/Hyperactivity Disorder. In Proceedingsof the International Conference on Image Analysis and Recognition, Lecture Notes in Computer Science, Springer-Verlag 2012.