Intelligent Heart Disease Prediction System Using Multi Atlas Segmentation
Abstract
The evaluation of ventricular function is important for the diagnosis of cardiovascular diseases. It involves the measurement o f the left ventricular (LV) mass. In this paper, a multi atlas segmentation method is proposed for cardiac magnetic resonance (MR) image segmentation. The proposed method is novel in two aspects. First, it formulates a patch-based label fusion model in a Bayesian framework. Second, it improves Image registration accuracy by utilizing label information, which improves image segmentation accuracy. The proposed method was evaluated on a cardiac MR Images set of 28 subjects. The results show that the proposed method is able to provide accurate information for clinical diagnosis.
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J.Cousty, L.Najman, M. Couprie, S. Clément-Guinaudeau, T. Goissen,And J. Garot, “Segmentation of 4D cardiac MRI: Automated method Based on spatio-temporal watershed cuts,” Image Vis. Comput., Vol.28, no. 8, 1229-1243,2010.
M. Jolly, “Fully automatic left ventricle segmentation in cardiacCine MR Images using registration and minimum surfaces,” MIDAS J. – Cardiac MR Left Ventricle Segment Chall.,2009.
M. Lorenzo-Valdés, G. I. Sanchez-Ortiz, A. G. Elkington, R. H. Mohiaddin,And D. Rueckert, “Segmentation of 4D cardiacMRimages usinga probabilistic atlas and the EM algorithm,” Med. Image Anal., vol. 8 no. 3, pp. 255-265, 2004.
M. Lynch, O. Ghita, and P. F. Whelan, “Segmentation of the left ventricle of the heart in 3- MRI data using an optimized NonrigidTemporal model,” IEEE Trans. Med. Image., vol.27,no.2,pp. 195-203, Feb. 2008.
C. Petitjean and J. N. Dacher, “A review of segmentation methodsIn short axis cardiac MR images,” Med Image Anal., vol. 15 ,pp. 169-184,2011.
H.Zang, A.Wahle,R.K.Johnson, T. D. Scholz, and M. Sonka, “4-D cardiac MR image analysis: Left and Right ventricular Morphology and function,” IEEE Trans. Med. Image., vol.29, no. 2,pp.350-364, Feb 2010.
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