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An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model

K.Vanitha 1 , M. Suresh Kumar2 , Sk. Althaf Rahaman3

  1. Department of Computer Science, GITAM (Deemed to be UNIVERSITY),Visakhapatnam, INDIA.
  2. Department of Computer Science, GITAM (Deemed to be UNIVERSITY),Visakhapatnam, INDIA.
  3. Department of Computer Science, GITAM (Deemed to be UNIVERSITY),Visakhapatnam, INDIA.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-3 , Page no. 225-229, Mar-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i3.225229

Online published on Mar 30, 2018

Copyright © K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman . 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: K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman, “An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.3, pp.225-229, 2018.

MLA Style Citation: K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman "An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model." International Journal of Computer Sciences and Engineering 6.3 (2018): 225-229.

APA Style Citation: K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman, (2018). An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model. International Journal of Computer Sciences and Engineering, 6(3), 225-229.

BibTex Style Citation:
@article{Kumar_2018,
author = {K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman},
title = {An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2018},
volume = {6},
Issue = {3},
month = {3},
year = {2018},
issn = {2347-2693},
pages = {225-229},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1787},
doi = {https://doi.org/10.26438/ijcse/v6i3.225229}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i3.225229}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1787
TI - An Effective Segmentation Approach of Medical Images Based on Beta Mixture Model
T2 - International Journal of Computer Sciences and Engineering
AU - K.Vanitha, M. Suresh Kumar, Sk. Althaf Rahaman
PY - 2018
DA - 2018/03/30
PB - IJCSE, Indore, INDIA
SP - 225-229
IS - 3
VL - 6
SN - 2347-2693
ER -

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Abstract

Image segmentation aims at investigating and the Images with respect to the pattern of the pixels. Many Models are addressed in this direction. Among the various focused areas of segmentation, medical segmentation has gained importance; this is due to the fact that proper categorization of the pixels helps in the identification of the diseases. However, for successful segmentation one require to judge suitable features. In this paper, mainly we are proposing a Bivariate Beta Mixture Model (BMM) for segmenting the medical images by considering the Bivariate features. In order to implement the model, Berkley Bench Mark dataset is considered. This proposed model Performance is evaluated by using PSNR, MSE, IF, Average difference (AD).

Key-Words / Index Term

Beta Mixture Model, Berkley Images, IF, PSNR, MSE, Image Segmentation

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