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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1552
No. of Authors : 4025
  Journal Paper


Paper Title :
Field Programmable Gate Array Based Real Time Brain Image Segmentation for Medical Record Processing

Author :Yaswanth Kumar Avulapati, R.Seshadri, C.S.Gnana Sudha, A.Sai Sreenivasulu, P.Tulasi Krishna

Article Citation :Yaswanth Kumar Avulapati ,R.Seshadri ,C.S.Gnana Sudha ,A.Sai Sreenivasulu ,P.Tulasi Krishna , (2013 ) " Field Programmable Gate Array Based Real Time Brain Image Segmentation for Medical Record Processing " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 33-37, Volume-1,Issue-9

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

Type : Research paper

Published : Volume-1,Issue-9


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