A Probabilistic Segmentation Method for the Identification of Luminal Borders in Intravascular Ultrasound Images
Abstract
Intravascular ultrasound (IVUS) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels and is particularly useful for studying atherosclerosis. In this paper, we present a probabilistic approach for the semi-automatic identification of the luminal border on IVUS images. Specifically, we parameterize the lumen contour using a mixture of Gaussian that is deformed by the minimization of a cost function formulated using a probabilistic approach. For the optimization of the cost function, we introduce a novel method that linearly combines the descent directions of the steepest descent and BFGS optimization methods within a trust region that improves convergence. Results of our proposed method on 20 MHz IVUS images are presented and discussed in order to demonstrate the effectiveness of our approach.
Cite
Text
Ruiz et al. "A Probabilistic Segmentation Method for the Identification of Luminal Borders in Intravascular Ultrasound Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587484Markdown
[Ruiz et al. "A Probabilistic Segmentation Method for the Identification of Luminal Borders in Intravascular Ultrasound Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/ruiz2008cvpr-probabilistic/) doi:10.1109/CVPR.2008.4587484BibTeX
@inproceedings{ruiz2008cvpr-probabilistic,
title = {{A Probabilistic Segmentation Method for the Identification of Luminal Borders in Intravascular Ultrasound Images}},
author = {Ruiz, Eduardo Gerardo Mendizabal and Rivera, Mariano and Kakadiaris, Ioannis A.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2008},
doi = {10.1109/CVPR.2008.4587484},
url = {https://mlanthology.org/cvpr/2008/ruiz2008cvpr-probabilistic/}
}