Name
Abstract | ||
|---|---|---|
Computed tomography angiography (CTA) is a powerful tool for the diagnosis of vascular diseases and its radiation dose is widely concerned. Limited scan within vessel region, deemed as region-of-interest (ROI), is a particularly apt dose reduction strategy for CTA since clinical assessment mainly depends on vessel structures. However, insufficient raw data may induce noise and artifacts in images reconstructed by conventional analytic and iterative methods. In this paper, we introduced an ultra-low-dose scan protocol for CTA, by modifying the contrast-enhanced stage with a low-mA, few-view ROI scan. Accordingly, a previous-stage-based ROI reconstruction method (PSBROI) was proposed with weighted projections and voxels and a dual-dictionary learning (DDL) strategy. Experiments showed that under the ultra-low-dose scan protocol, the proposed method performed better in artifact removal, noise suppression and structure preservation within ROI than the conventional methods. The ultra-low-dose scan with 30 mAs, 60 projection views and 34.1 mm ROI size could reduce dose to about 0.305% of normal dose. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/BIBE50027.2020.00164 | 2020 IEEE 20TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE 2020) |
Keywords | DocType | ISSN |
CT imaging, ROI reconstruction, compressed sensing, ultra-low-dose CT Angiography | Conference | 2471-7819 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuffi Zhou | 1 | 0 | 0.34 |
| Xinzhen Zhang | 2 | 0 | 0.34 |
| Weikang Zhang | 3 | 8 | 2.17 |
| Jianqi Sun | 4 | 0 | 1.35 |
| Jun Zhao | 5 | 92 | 16.79 |