title: [An approach for segmentation of X-ray angiographic image based on region-growing and structure inferring].
abstract: We presented a new method for vessel segmentation and vascular structure recognition for coronary angiographic images. During vessel segmentation, a new vessel function was proposed to attain vessel feature map. Then the region growing algorithm was implemented with an automatic selection of seed point, extraction of main vessel branch, and vessel detail repairing. In the algorithm of vascular structure recognition, a fuzzy operator was used, which can detect the structures of vascular segments, bifurcations, crosses, and tips. The experimental results indicated that there was about 5 percent larger vessel region which was extracted by the proposed segmentation method than that by the simple region growing algorithm, and several thinner vessels were resumed from the lower gray region. The results also indicated that the fuzzy operator could correctly infer the simulative and real vessel structure with 100% and 90.59% correctness rate on the average, respectively.
authors.forename: Chuan
authors.initials: C
authors.lastname: Mei
authors.forename: Guiliang
authors.initials: G
authors.lastname: Wu
authors.forename: Yuan
authors.initials: Y
authors.lastname: Yang
authors.forename: Lan
authors.initials: L
authors.lastname: Xie
authors.forename: Jiaju
authors.initials: J
authors.lastname: He
authors.forename: Shaolin
authors.initials: S
authors.lastname: Li
authors.forename: Shoujun
authors.initials: S
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D017023:Coronary Angiography; D006801:Humans; D011856:Radiographic Image Enhancement / Q000379:methods*; D014965:X-Rays