Name
Title | ||
|---|---|---|
Improving perfusion defect detection with respiratory motion compensation in cardiac SPECT |
Abstract | ||
|---|---|---|
In cardiac perfusion SPECT, respiratory motion can lead to non-uniform blur in the reconstructed myocardium. In addition, due to the irregularity in respiratory patterns, the acquired data with magnitude-binning for respiratory correction can exhibit high variability among both bin intervals and acquisition angles. In this study, we investigate the benefit of a motion correction scheme with acquisition time compensation for the task of perfusion defect detection in clinical acquisitions. We evaluated the detectability of perfusion defects in reconstructed images by using the total perfusion deficit scores obtained from a clinical model observer. The results show that with motion correction the area under the ROC curve is improved from 0.798 (without correction) to 0.835 (p-value <; 0.001). We also evaluated the reconstruction scheme with imaging dose reduced to 50%, 25%, and 12.5% of standard dose, and similar improvement is obtained with the correction scheme. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISBI.2018.8363584 | 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) |
Keywords | Field | DocType |
Respiratory motion correction,cardiac SPECT,perfusion defect detection | Nuclear medicine,Computer vision,Bin,Computer science,Respiratory motion,Dose Reduced,Respiratory system,Artificial intelligence,Area under the roc curve,Observer (quantum physics),Motion correction,Perfusion | Conference |
ISSN | ISBN | Citations |
1945-7928 | 978-1-5386-3637-4 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Song | 1 | 100 | 15.52 |
| Yongyi Yang | 2 | 1409 | 140.74 |
| Albert J. Ramon | 3 | 0 | 0.68 |
| Miles N. Wernick | 4 | 595 | 61.13 |
| P. Hendrik Pretorius | 5 | 22 | 9.04 |
| Michael A King | 6 | 115 | 27.84 |