DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-1,Issue-9 ( Nov, 2013 ) | |||||||||
Paper Title |
Field Programmable Gate Array Based Real Time Brain Image Segmentation for Medical Record Processing | |||||||||
Author Name |
Yaswanth Kumar Avulapati, R.Seshadri, C.S.Gnana Sudha, A.Sai Sreenivasulu, P.Tulasi Krishna | |||||||||
Affilition |
Dept of Computer Science,S.V.University,Tirupati, S.V.U.Computer Center,S.V.University,Tirupati 3Dept of statistics & Computer Science, K.V.A.F.S.University,Banglore, Dept of CSE,C.R.Engineering College,Tirupati, Dept of CSE,SKIT,Srikalahasthi | |||||||||
Pages |
33-37 | |||||||||
Abstract |
Abstract:-Medical imaging often involves the injection of contrast agents and subsequent analysis of tissue enhancement patterns. X-ray angiograms are projections of 3D reality into 2D representations; there is a fair amount of self occlusion among the vessels. Hence one cannot extract the vessels directly using the image intensities or gradients (edge) alone. Vessel extraction from angiogram images is useful for blood vessels measurement and computer visualizations of the coronary artery. This project describes the algorithm for automatic segmentation of coronary arteries in digital X-ray projections (coronary angiograms) The pattern recognition technique used in this project is K-Means clustering. In this technique clusters are formed based on the minimum distance criteria with random seed point selection. As the dataset’s scale increases rapidly, it is difficult to use K-means and deal with massive data, so an improved K-means algorithm is proposed. The performance of the proposed algorithm is compared with other techniques | |||||||||
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