Investigation of edge detection techniques based on coronary angiography images

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Date
2017-06
Authors
Basaier Jialade
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Often, low quality medical X-ray images are produced due to the least possible amount of projection used to form the images. Minimum projection beams are used to reduce damage to patients’ body. Angiography is an important class of medical imaging. The image is obtained using X-ray techniques after a contrast agent is injected into the patient’s blood vessels. Coronary angiography is a critical type of angiography images and it could be used to diagnose serious heart and artery diseases. However, most angiography images suffer from non-uniform illumination and noises, which makes it difficult for doctors to make accurate diagnoses. Therefore, processing of angiograms is necessary to make them more visible thus help doctors to produce more accurate diagnoses in a shorter time. In this project, the angiogram is firstly enhanced using histogram equalization. Then five edge detection techniques including Roberts cross, Prewitt, Sobel, Canny, and a modified Sobel algorithm are implemented. The main aim is to clearly delineate edges of the blood vessels, and the Sobel operator is found to be the most suitable algorithm for analyzing coronary angiography images based on the quantitative and qualitative evaluations.
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