ArticlePhysics in medicine and biology2018
Time-resolved C-arm cone beam CT angiography (TR-CBCTA) imaging from a single short-scan C-arm cone beam CT acquisition with intra-arterial contrast injection.
Article in Physics in medicine and biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Dual-Layer Detector Cone-Beam CT Angiography for Stroke Assessment: First-in-Human Results (the Next Generation X-ray Imaging System Trial).AJNR. American journal of neuroradiology · 2023Article
- An Enhanced SMART-RECON Algorithm for Time-Resolved C-Arm Cone-Beam CT Imaging.IEEE transactions on medical imaging · 2020Article
- Measurements of cerebral blood volume using quantitative susceptibility mapping, RNMR in biomedicine · 2019Article
- An Empirical Data Inconsistency Metric (DIM) Driven CT Image Reconstruction Method.IEEE transactions on medical imaging · 2019Article
- Quantification of temporal resolution improvement factor in SMART-RECON based time-resolved C-arm Cone beam computed tomography angiography (TR-CBCTA).Physics in medicine and biology · 2018Article
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8 authors.
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Abstract
Time-resolved C-arm cone-beam CT (CBCT) angiography (TR-CBCTA) images can be generated from a series of CBCT acquisitions that satisfy data sufficiency condition in analytical image reconstruction theory. In this work, a new technique was developed to generate TR-CBCTA images from a single short-scan CBCT data acquisition with contrast media injection. The reconstruction technique enabling this application is a previously developed image reconstruction technique, synchronized multi-artifact reduction with tomographic reconstruction (SMART-RECON). In this new application, the acquired short-scan CBCT projection data were sorted into a union of several sub-sectors of view angles and each sub-sector of view angles corresponds to an individual image volume to be reconstructed. The SMART-RECON method was then used to jointly reconstruct all of these individual image volumes under two constraints: (1) each individual image volume is maximally consistent with the measured cone-beam projection data within the corresponding view angle sector and (2) the nuclear norm of the image matrix is minimized. The difference between these reconstructed individual image volumes is used to generated the desired subtracted angiograms. To validate the technique, numerical simulation data generated from a fractal tree angiogram phantom were used to quantitatively study the accuracy of the proposed method and retrospective in vivo human subject studies were used to demonstrate the feasibility of generating TR-CBCTA in clinical practice.
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