Abstract
Digital subtraction angiography (DSA) is one of imaging methods using X-ray image for clear visualization of the vessel information during intervention with a catheter. In order to obtain a fine DSA image, patients have to hold their breathing. However, steady breath hold is a burden for the patients and is sometimes difficult for elder patients. We propose a blood vessel enhancement method with consecutive digital angiographic images acquired under the natural breathing. Robust principal component analysis (RPCA) is used to enhance blood vessel information from consecutive angiographic images acquired under the natural breathing. RPCA can separate the consecutive images into a low-rank component and a sparse component. The information of contrast media is included in the sparse component. We implemented it on GPU and applied the proposed method to 13 sets of angiographic images and confirmed that it enables to generate satisfactory enhanced angiographic images.
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This work was supported in part JSPS KAKENHI (16K16406) and the JSPS Core-to-Core Program.
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Kawabe, M. et al. (2020). Blood Vessel Enhancement in Liver Region from a Sequence of Angiograms Taken under Free Breathing. In: Cree, M., Huang, F., Yuan, J., Yan, W. (eds) Pattern Recognition. ACPR 2019. Communications in Computer and Information Science, vol 1180. Springer, Singapore. https://doi.org/10.1007/978-981-15-3651-9_13
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DOI: https://doi.org/10.1007/978-981-15-3651-9_13
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