Conference proceeding
Multidimensional segmentation of coronary intravascular ultrasound images using knowledge-based methods
Proceedings of SPIE, Vol.5747(1), pp.496-504
Medical Imaging 2005: Image Processing
04/29/2005
DOI: 10.1117/12.595850
Abstract
In vivo studies of the relationships that exist among vascular geometry, plaque morphology, and hemodynamics have recently been made possible through the development of a system that accurately reconstructs coronary arteries imaged by x-ray angiography and intravascular ultrasound (IVUS) in three dimensions. Currently, the bottleneck of the system is the segmentation of the IVUS images. It is well known that IVUS images contain numerous artifacts from various sources. Previous attempts to create automated IVUS segmentation systems have suffered from either a cost function that does not include enough information, or from a non-optimal segmentation algorithm. The approach presented in this paper seeks to strengthen both of those weaknesses -- first by building a robust, knowledge-based cost function, and then by using a fully optimal, three-dimensional segmentation algorithm. The cost function contains three categories of information: a compendium of learned border patterns, information theoretic and statistical properties related to the imaging physics, and local image features. By combining these criteria in an optimal way, weaknesses associated with cost functions that only try to optimize a single criterion are minimized. This cost function is then used as the input to a fully optimal, three-dimensional, graph search-based segmentation algorithm. The resulting system has been validated against a set of manually traced IVUS image sets. Results did not show any bias, with a mean unsigned luminal border positioning error of 0.180 ± 0.027 mm and an adventitial border positioning error of 0.200 ± 0.069 mm.
Details
- Title: Subtitle
- Multidimensional segmentation of coronary intravascular ultrasound images using knowledge-based methods
- Creators
- Mark E Olszewski - Univ. of Iowa (USA)Andreas Wahle - Univ. of Iowa (USA)Sarah C Vigmostad - Univ. of Iowa (USA)Milan Sonka - Univ. of Iowa (USA)
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.5747(1), pp.496-504
- Conference
- Medical Imaging 2005: Image Processing
- DOI
- 10.1117/12.595850
- ISSN
- 0277-786X
- Language
- English
- Date published
- 04/29/2005
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Surgery; Radiation Oncology; Injury Prevention Research Center; Mechanical Engineering; Ophthalmology and Visual Sciences
- Record Identifier
- 9984047603902771
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