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Volume 6, 2017, Issue 9, Pages 174-185; Paper doi: 10.15412/J.JBTW.01060903; Paper ID: 15494.
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A Fast and Efficient Region based Aneurysm Segmentation Model for Medical Image Segmentation
(Research Paper)
  • 1 Department of ECE, Aditya College of Engineering, Surampalem, A.P., India
  • 2 Department of ECE, University College of Engineering Vizianagram, JNTUK, Vizianagarm, A.P., India
  • Correspondence should be addressed to Srinivas Thirumala, Department of ECE, Aditya College of Engineering, Surampalem, A.P., India; Tel: ; Fax: ; Email: tirumala.sri1@gmail.com.
  • Correspondence two Co-correspondence should be addressed to Srinivasa Rao Chanamallu, Department of ECE, University College of Engineering Vizianagram, JNTUK, Vizianagarm, A.P., India; Tel: ; Fax: ; Email: ch_rao@rediffmail.com.

Abstract

Aneurysm and blood vessel delineation from medical images facilitates efficient diagnosis of the Aneurysm and vessels (Stroke or Hemorrhage and Stenosis or malformations) and registration of patient images obtained at different times. Computer-aided diagnosis and detection of Aneurysms via Segmentation algorithms is a complex and multi-faceted issue in medical image processing, as adjoining vessels are the high-intensity structures whereas aneurysms are of low contrast and intensity. Obviously, segmentation is essential to identify the disease severity by change monitoring and also to know further Haemo-dynamic situation in critical cases. Change detection and further analysis gives the complete picture of the case of interest. For Brain tumor detection and analysis, there are several segmentation algorithms but only few are suitable for aneurysm detection and analysis. There is a necessity to provide an efficient segmentation model for aneurysm analysis, change detection and delineation which overcomes the limitations on speed and accuracy of other models. The objective of this paper is to first, apply local binary fitting (LBF), chan-vese (CV) models to aneurysm analysis. Then perform Region based Aneurysm Segmentation model frame work on data sheets of MR Angiography of brain. It is a perfect level set based Active contour model which converges in short span without requirement of any stability and termination criterions. The key feature of this model is that delineation is independent of choice of mask dimensions. Promising results are obtained with the proposed model.

Keywords

Active Contours, Chan-Vese Model, LBF, Level set Method, Ruptured Aneurysm

Paper Title: A Fast and Efficient Region based Aneurysm Segmentation Model for Medical Image Segmentation
Paper Details: Volume 6, Issue 9, Pages: 174-185
Paper doi:10.15412/J.JBTW.01060903
Journal of Biology and Today's World
Journal home page: http://journals.lexispublisher.com/jbtw
Copyright © 2017 Srinivas Thirumala et al. This is an open access paper distributed under the Creative Commons Attribution License.
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