Segmentation of ulcerated plaque: evaluation and optimization of a semiautomatic method for tracking the progression of carotid atherosclerosis

Jeremy D. Gill; Hanif M. Ladak; Aaron Fenster

doi:10.1117/12.431014

3 July 2001 Segmentation of ulcerated plaque: evaluation and optimization of a semiautomatic method for tracking the progression of carotid atherosclerosis

Jeremy D. Gill, Hanif M. Ladak, Aaron Fenster

Author Affiliations +

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431014
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

A semi-automatic method for segmenting carotid lumen and plaque from three-dimensional vascular ultrasound (US) images has been developed. We examine its ability to distinguish changes in carotid vessel and plaque surface morphology, such as those caused by plaque ulceration. Two stenosed vessel phantoms were imaged using a 3D US imaging system. The phantoms were identical except for the inclusion of a hemispherical cut in the side of one of the vessels, in order to simulate the development of an ulceration. Ultrasound images of the phantoms were segmented using our algorithm, then the resulting surfaces were registered to one another using a rigid-body iterative closest point (ICP) algorithm. The volume of ulceration was determined by finding the difference between the two segmented surfaces in a region of interest surrounding the ulceration. Since the true volume of the ulceration was known a priori, an optimization strategy was used to tune the deformable model to better segment the ulceration. Analysis of ulceration volume as a function of the deformable model's parameters show that 1) large ulcerations are easily identified in our test case, and 2) the model is well behaved with respect to its parameters, suggesting that an automatic strategy for volumetric optimization is feasible.

Citation Download Citation

Jeremy D. Gill, Hanif M. Ladak, and Aaron Fenster "Segmentation of ulcerated plaque: evaluation and optimization of a semiautomatic method for tracking the progression of carotid atherosclerosis", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431014

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