caa a22 4500 605539251 CHVBK 20210128100906.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s10396-014-0559-3 doi (NATIONALLICENCE)springer-10.1007/s10396-014-0559-3 Tumor boundary detection in ultrasound imagery using multi-scale generalized gradient vector flow [Elektronische Daten] [Yi Le, Xianze Xu, Li Zha, Wencheng Zhao, Yanyan Zhu] Purpose: As a key technology in high-intensity focused ultrasound (HIFU) ablation systems, a precise ultrasound image segmentation method for tumor boundary detection is helpful for ablation of tumors and avoiding tumor recurrence. This study explores a new deformable snake model called multi-scale generalized gradient vector flow (MS-GGVF) to segment ultrasound images in HIFU ablation. Methods: The main idea of the technique is dealing with two issues including spurious boundary attenuation and setting the standard deviation of the Gaussian filter. We assign the standard deviation as scales to build the MS-GGVF model and create a signed distance map to use its gradient direction information and magnitude information to refine the multi-scale edge map by attenuating spurious boundaries and highlighting the real boundary. In addition, a fast generalized gradient vector flow computation algorithm based on an augmented Lagrangian method is introduced to calculate the external force vector field to improve the computation efficiency of our model. Results: The experimental segmentations were similar to the ground truths delineated by two medical physicians with high area overlap measure and low mean contour distance. Conclusion: The experimental results demonstrate that the proposed algorithm is robust, reliable, and precise for tumor boundary detection in HIFU ablation systems. The Japan Society of Ultrasonics in Medicine, 2014 HIFU ablation system nationallicence Generalized gradient vector flow nationallicence Tumor boundary detection nationallicence Distance map nationallicence Multi-scale edge map nationallicence Le Yi Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut Xu Xianze Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut Zha Li Ultrasonic Department, Hubei Cancer Hospital, 116 Zhuodaoquan South Road, Wuchang District, 430079, Wuhan, China aut Zhao Wencheng Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut Zhu Yanyan Ultrasonic Department, Hubei Cancer Hospital, 116 Zhuodaoquan South Road, Wuchang District, 430079, Wuhan, China aut Journal of Medical Ultrasonics Springer Japan 42/1(2015-01-01), 25-38 1346-4523 42:1<25 2015 42 10396 https://doi.org/10.1007/s10396-014-0559-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10396-014-0559-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Le Yi Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut NATIONALLICENCE 700 1- Xu Xianze Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut NATIONALLICENCE 700 1- Zha Li Ultrasonic Department, Hubei Cancer Hospital, 116 Zhuodaoquan South Road, Wuchang District, 430079, Wuhan, China aut NATIONALLICENCE 700 1- Zhao Wencheng Electronic Information School, Wuhan University, 16 Luojiashan Road, Wuchang District, 430079, Wuhan, China aut NATIONALLICENCE 700 1- Zhu Yanyan Ultrasonic Department, Hubei Cancer Hospital, 116 Zhuodaoquan South Road, Wuchang District, 430079, Wuhan, China aut NATIONALLICENCE 773 0- Journal of Medical Ultrasonics Springer Japan 42/1(2015-01-01), 25-38 1346-4523 42:1<25 2015 42 10396