title: Adaptive Kalman snake for semi-autonomous 3D vessel tracking.
abstract: In this paper, we propose a robust semi-autonomous algorithm for 3D vessel segmentation and tracking based on an active contour model and a Kalman filter. For each computed tomography angiography (CTA) slice, we use the active contour model to segment the vessel boundary and the Kalman filter to track position and shape variations of the vessel boundary between slices. For successful segmentation via active contour, we select an adequate number of initial points from the contour of the first slice. The points are set manually by user input for the first slice. For the remaining slices, the initial contour position is estimated autonomously based on segmentation results of the previous slice. To obtain refined segmentation results, an adaptive control spacing algorithm is introduced into the active contour model. Moreover, a block search-based initial contour estimation procedure is proposed to ensure that the initial contour of each slice can be near the vessel boundary. Experiments were performed on synthetic and real chest CTA images. Compared with the well-known Chan-Vese (CV) model, the proposed algorithm exhibited better performance in segmentation and tracking. In particular, receiver operating characteristic analysis on the synthetic and real CTA images demonstrated the time efficiency and tracking robustness of the proposed model. In terms of computational time redundancy, processing time can be effectively reduced by approximately 20%.
authors.affiliation: Department of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Republic of Korea(1). Electronic address: crere@yonsei.ac.kr.
authors.forename: Sang-Hoon
authors.initials: SH
authors.lastname: Lee
authors.affiliation: Department of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Republic of Korea(1). Electronic address: slee@yonsei.ac.kr.
authors.forename: Sanghoon
authors.initials: S
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods*; D001808:Blood Vessels / Q000033:anatomy & histology*; D006801:Humans; D008962:Models, Theoretical
keywords: Active contour; Adaptive control points spacing; Initial contour estimation; Kalman filter; Snake; Vessel tracking