Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

This paper deals with the 3D reconstruction of sparse data in X-ray rotational imaging. Due to the cardiac motion, the number of available projections for this reconstruction is equal to four, which leads to a strongly under-sampled reconstruction problem. We address thus this illness problem throug...

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Bibliographic Details
Main Authors: Hu, Y., Jung, M., Oukili, A., Yang, G., Nunes, J.-C, Fehrenbach, J., Peyre, G., Bedossa, M., Luo, L., Toumoulin, C., Cohen, L. D.
Format: Conference Proceeding
Language:English
Subjects:
Active contours
Angiography
Computational modeling
Estimation
Image reconstruction
Image segmentation
Level set
Maximum a posteriori (MAP)
minimal path
non-local active contours
reconstruction
X-ray rotational coronary angiography
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Summary:This paper deals with the 3D reconstruction of sparse data in X-ray rotational imaging. Due to the cardiac motion, the number of available projections for this reconstruction is equal to four, which leads to a strongly under-sampled reconstruction problem. We address thus this illness problem through a regularized iterative method. The whole algorithm is divided into two steps. Firstly, a minimal path segmentation step extracts artery tree boundaries. Secondly, a MAP reconstruction comparing L0-norm and L1-norm priors is applied on this extracted coronary tree. The reconstruction optimization process relies on a separable paraboloidal (SPS) algorithm. Some preliminary results are provided on simulated rotational angiograms.
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2012.6235670