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dc.contributor.authorKrit Somkanthaen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.description.abstractThis paper presents a novel edge following technique for image segmentation designed to segment the left ventricle in cardiac magnetic resonance (MR) images. This is a required step to determine the volume of left ventricle in a cardiac MR image, which is an essential tool for cardiac diagnosis. The traditional method for extracting them from cardiac MR images is by human delineation. This method is accuracy but time consuming. So a new ventricular segmentation technique is proposed in order to reduce the analysis time with similar accuracy level compared to doctors' opinions. Our proposed technique can detect ventricle edges in MR images using the information from the vector image model and the edge map. We also compare the proposed segmentation technique with the active contour model (ACM) and the gradient vector flow (GVF) by using the opinions of two skilled doctors as the ground truth. The experimental results show that our technique is able to provide more accurate segmentation results than the classical contour models and visually close to the manual segmentation by the experts. The results evaluated using a numerical measure by mean of the probability of error in image segmentation also confirm the visual evaluation. © 2008 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleLeft ventricular segmentation of cardiac magnetic resonance images using a novel edge following techniqueen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2008 IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2008en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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