title: A snake-based method for segmentation of intravascular ultrasound images and its in vivo validation.
abstract: Image segmentation for detection of vessel walls is necessary for quantitative assessment of vessel diseases by intravascular ultrasound. A new segmentation method based on gradient vector flow (GVF) snake model is proposed in this paper. The main characteristics of the proposed method include two aspects: one is that nonlinear filtering is performed on GVF field to reduce the critical points, change the morphological structure of the parallel curves and extend the capture range; the other is that balloon snake is combined with the model. Thus, the improved GVF and balloon snake can be automatically initialized and overcome the problem caused by local energy minima. Results of 20 in vivo cases validated the accuracy and stability of the segmentation method for intravascular ultrasound images.
authors.affiliation: Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.
authors.forename: Xinjian
authors.initials: X
authors.lastname: Zhu
authors.forename: Pengfei
authors.initials: P
authors.lastname: Zhang
authors.forename: Jinhua
authors.initials: J
authors.lastname: Shao
authors.forename: Yuanzhi
authors.initials: Y
authors.lastname: Cheng
authors.forename: Yun
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jing
authors.initials: J
authors.lastname: Bai
mesh_terms: D000465:Algorithms; D000818:Animals; D050197:Atherosclerosis / Q000000981:diagnostic imaging*; D004195:Disease Models, Animal; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D011817:Rabbits; D015203:Reproducibility of Results; D018084:Ultrasonography, Interventional