The Segmentation Method Based on Fusion Algorithm of Transition Region Extraction for Coronary Angiograms

Abstract

Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. Firstly, the coronary arteries are extracted by using the local complexity method based on Top-hat. Then the coronary arteries are extracted again by using the local complexity method based on Gaussian filter. Finally, the segmentation image is obtained by fusing two extracted coronary arteries images. The experiments indicate that the proposed method has better performance on the small vessels extraction and background elimination. In addition, the method is valuable for diagnosis and the quantitative analysis of vessels.

Entropy-Based Automatic Segmentation of Bones in Digital X-ray Images

“…This boundary enhancement aids thresholding for segmentation of the transition region from the image. Kang et al used local entropy values to identify transition regions on region extraction from coronary angiograms [14].…”