Abstract
Automatic vessel extraction from X-ray angiograms (XA) for percutaneous coronary interventions is often hampered by low contrast and presence of background structures, e.g. diaphragm, guiding catheters, stitches. In this paper, we present a novel layer separation technique for vessel enhancement in XA to address this problem. The method uses morphological filtering and Robust PCA to separate interventional XA images into three layers, i.e. a large-scale breathing structure layer, a quasi-static background layer and a layer containing the vessel structures that could potentially improve the quality of vessel extraction from XA. The method is evaluated on several clinical XA sequences. The result shows that the proposed method significantly increases the visibility of vessels in XA and outperforms other background-removal methods.
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Notes
- 1.
The implementation is available at http://perception.csl.illinois.edu/matrix-rank/sample_code.html.
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Acknowledgements
The authors wish to acknowledge financial support from Technology Foundation STW IMAGIC project under iMIT program Grant No. 12703.
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Ma, H. et al. (2015). Layer Separation for Vessel Enhancement in Interventional X-ray Angiograms Using Morphological Filtering and Robust PCA. In: Linte, C., Yaniv, Z., Fallavollita, P. (eds) Augmented Environments for Computer-Assisted Interventions. AE-CAI 2015. Lecture Notes in Computer Science(), vol 9365. Springer, Cham. https://doi.org/10.1007/978-3-319-24601-7_11
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DOI: https://doi.org/10.1007/978-3-319-24601-7_11
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