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A snake-based method for segmentation of intravascular ultrasound images and its in vivo validation |
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| Authors: | Xinjian Zhu Pengfei ZhangJinhua Shao Yuanzhi ChengYun Zhang Jing Bai |
| Affiliation: | a Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China b Fifth Laboratory, Research Institute of Field Surgery, Daping Hospital, Third Military Medical University of Chinese PLA, State Key Laboratory for Trauma, Burn and Combined Injury, Chongqing 400042, China c Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education and Chinese Ministry of Health, Shandong University Qilu Hospital, Jinan 250012, China |
| 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. |
| Keywords: | Segmentation Intravascular ultrasound GVF snake Nonlinear filtering Balloon snake |
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