Completely automated multiresolution edge snapper—a new technique for an accurate carotid ultrasound IMT measurement: clinical validation and benchmarking on …
The aim of this paper is to describe a novel and completely automated technique for carotid
artery (CA) recognition, far (distal) wall segmentation, and intima-media thickness (IMT)
measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases.
The architecture of completely automated multiresolution edge snapper (CAMES) consists of
the following two stages: 1) automated CA recognition based on a combination of scale-
space and statistical classification in a multiresolution framework and 2) automated …
artery (CA) recognition, far (distal) wall segmentation, and intima-media thickness (IMT)
measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases.
The architecture of completely automated multiresolution edge snapper (CAMES) consists of
the following two stages: 1) automated CA recognition based on a combination of scale-
space and statistical classification in a multiresolution framework and 2) automated …
Completely automated multiresolution edge snapper (CAMES): A new technique for an accurate carotid ultrasound IMT measurement and its validation on a multi …
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 CALEX 3), 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 …
(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 CALEX 3), 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 …