# Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization

arXiv: https://arxiv.org/abs/2207.13837 · HTML: https://mlsanity.com/paper/2207.13837/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 15 references that are in the map.
- First posted on arXiv 28 Jul 2022.

## Built on by (most cited first, 1 of 1)

- [A Novel Coronary Artery Registration Method Based on Super-pixel Particle Swarm Optimization](https://mlsanity.com/paper/2505.24351/) (2025)

## Abstract (arXiv)

We present a method to extract coronary vessels from fluoroscopic x-ray sequences. Given the vessel structure for the source frame, vessel correspondence candidates in the subsequent frame are generated by a novel hierarchical search scheme to overcome the aperture problem. Optimal correspondences are determined within a Markov random field optimization framework. Post-processing is performed to extract vessel branches newly visible due to the inflow of contrast agent. Quantitative and qualitative evaluation conducted on a dataset of 18 sequences demonstrates the effectiveness of the proposed method.