Automatic medical image segmentation based on finite skew Gaussian mixture model
Joint Authors
Vadaparthi, Nagesh
Yerramalli, Srinivas
Penumatsa, Suresh
Poosapati, Sitharama
Source
The International Arab Journal of Information Technology
Issue
Vol. 13, Issue 5 (30 Sep. 2016), pp.501-508, 8 p.
Publisher
Publication Date
2016-09-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Engineering & Technology Sciences (Multidisciplinary)
Abstract EN
novel methodology for segmenting the brain Magnetic Resonance Imaging (MRI) images using the finite skew Gaussian mixture model has been proposed for improving the effectiveness of the segmentation process.
This model includes Gaussian mixture model as a limiting case and we believe does more effective segmentation of both symmetric and asymmetric nature of brain tissues as compared to the existing models.
The segmentation is carried out by identifying the initial parameters and utilizing the Expectation-Maximization (EM) algorithm for fine tuning the parameters.
For effective segmentation, hierarchical clustering technique is utilized.
The proposed model has been evaluated on the brain images extracted from the brain web image database using 8sub-images of 2 brain images.
The segmentation evaluation is carried out using objective evaluation criterion viz.
Jacquard Coefficient (JC) and Volumetric Similarity (VS).
The performance evaluation of reconstructed images is carried out using image quality metrics.
The experimentation is carried out using T1 weighted images and the results are presented.
We infer from the results that the proposed model achieves good segmentation results when used in brain image processing.
American Psychological Association (APA)
Vadaparthi, Nagesh& Yerramalli, Srinivas& Penumatsa, Suresh& Poosapati, Sitharama. 2016. Automatic medical image segmentation based on finite skew Gaussian mixture model. The International Arab Journal of Information Technology،Vol. 13, no. 5, pp.501-508.
https://search.emarefa.net/detail/BIM-721995
Modern Language Association (MLA)
Vadaparthi, Nagesh…[et al.]. Automatic medical image segmentation based on finite skew Gaussian mixture model. The International Arab Journal of Information Technology Vol. 13, no. 5 (Sep. 2016), pp.501-508.
https://search.emarefa.net/detail/BIM-721995
American Medical Association (AMA)
Vadaparthi, Nagesh& Yerramalli, Srinivas& Penumatsa, Suresh& Poosapati, Sitharama. Automatic medical image segmentation based on finite skew Gaussian mixture model. The International Arab Journal of Information Technology. 2016. Vol. 13, no. 5, pp.501-508.
https://search.emarefa.net/detail/BIM-721995
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 506-507
Record ID
BIM-721995