Visual Hull-Based Approach for Coronary Vessel Three-Dimensional Reconstruction
Year: 2025
Type: article
Abstract: This paper addresses the problem of automatically reconstructing three-dimensional coronary vessel trees from a series of X-ray angiography images, a task which remains difficult, particularly with respect to solutions requiring no additional user input. This study analyses the performance of a visual hull-based algorithm, producing the actual positions of heart arteries in the coordinate system, which is an approach not sufficiently explored in XRA images analysis. The proposed algorithm first creates a bounding cube using a novel heuristic and then iteratively projects the cube onto preprocessed 2D images, removing points too far from the depicted arteries. The method performance is first evaluated on a synthetic dataset through a series of experiments, and for a set of common clinical angles, 3D Dice of 75.25% and 78.61% reprojection Dice is obtained, which rivals the state-of-the-art machine learning methods. The findings suggest that the method offers a promising and interpretable alternative to black box methods on the synthethic dataset in question.
Source: Applied Sciences
DOI: 10.3390/app151910450
Authors: Dominik Bernard Lau, Tomasz Dziubich
Institution: Gdańsk University of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4414556838