Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/23609
Title: | Completely automated multiresolution edge snapper (CAMES): A new technique for an accurate carotid ultrasound IMT measurement and its validation on a multi-institutional database | Authors: | Molinari, Filippo Loizou, Christos P. Zeng, Guang Pattichis, Constantinos S. Pantziaris, Marios Liboni, William Nicolaides, Andrew N. Suri, Jasjit S. |
Major Field of Science: | Engineering and Technology | Field Category: | Mechanical Engineering | Keywords: | Automated techniques;Carotid artery;Image frames;Integrated approach;Intima-media thickness;Measurement-based;Multi-resolution approach;Multi-resolutions | Issue Date: | Feb-2011 | Source: | SPIE Medical Imaging, 2011, 14–16 February, Lake Buena Vista (Orlando), Florida, United States | Journal: | SPIE Medical Imaging | Abstract: | Since 2005, our research team has been developing automated techniques for carotid artery (CA) wall segmentation and intima-media thickness (IMT) measurement. We developed a snake-based technique (which we named CULEX 1,2), a method based on an integrated approach of feature extraction, fitting, and classification (which we named CALEX3), and a watershed transform based algorithm4. Each of the previous methods substantially consisted in two distinct stages: Stage-I - Automatic carotid artery detection. In this step, intelligent procedures were adopted to automatically locate the CA in the image frame. Stage-II - CA wall segmentation and IMT measurement. In this second step, the CA distal (or far) wall is segmented in order to trace the lumen-intima (LI) and media-adventitia (MA) boundaries. The distance between the LI/MA borders is the IMT estimation. The aim of this paper is the description of a novel and completely automated technique for carotid artery segmentation and IMT measurement based on an innovative multi-resolution approach. | URI: | https://hdl.handle.net/20.500.14279/23609 | ISBN: | 9780819485045 | DOI: | 10.1117/12.877131 | Rights: | © SPIE | Type: | Conference Papers | Affiliation : | Politecnico di Torino Intercollege Mayo Clinic University of Cyprus Cyprus Institute of Neurology and Genetics Gradenigo Hospital Biomedical Technologies |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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