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2D Atlas and coronary detection of human heart for educational purposes

Human heart anatomy is the study of morphological structures and relationships between morphological structures. Hence such a study when visualized in the form of a two dimensional atlas can hold strong interactive sessions between doctors and medical students. Atlas is a visualization technique developed for understanding the morphological structures of a human body. Interacting directly with morphological structures contributes to a more comprehensive understanding of them in spatial relation to their surroundings. The purpose of this paper is to develop new interactive system, where the system provides a 2D atlas and artery detection of the human heart in detail. 2D atlas is created by using segmentation as a technique, where image segmentation is done to segment different parts of the morphological structures while performing structure analysis in the system. The segmentation algorithms used were K-Means, Watershed and Region Growing. Out of these three algorithms, region growing was considered to be the best because the algorithm was able to extract multiple regions of regions were then color masked for unique identification. By performing analytical study on different edge detection techniques such as Laplacian of Gaussian, Hessian, Frangi, Imoverlay (Sobel, Canny, Roberts and Prewitt), Thresholding (Global, Otsu, and Local), coronary artery was extracted from the given set of CT images of human heart. From the results produced by various algorithms, the doctor will decide which algorithm has given a better output based on visual perception and quality measures.