Name
Title | ||
|---|---|---|
Unsupervised PET logan parametric image estimation using conditional deep image prior |
Abstract | ||
|---|---|---|
•This is the first unsupervised deep learning method for the Logan parametric image estimation. No prior training nor high-quality training datasets are needed.•The anatomical image from the same subject’s CT or MR image can be used as an additional manifold constraint to further improve the parametric image quality.•Validation on both simulation and clinical patient datasets demonstrated that the proposed method can generate parametric images with more detailed structures and achieve higher contrast-to-noise improvement ratios. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.media.2022.102519 | Medical Image Analysis |
Keywords | DocType | Volume |
PET Parametric image estimation,Logan plot,Unsupervised learning,Deep image prior | Journal | 80 |
ISSN | Citations | PageRank |
1361-8415 | 0 | 0.34 |
References | Authors | |
2 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianan Cui | 1 | 0 | 1.01 |
| Kuang Gong | 2 | 0 | 1.01 |
| Ning Guo | 3 | 0 | 0.34 |
| Kyungsang Kim | 4 | 0 | 0.34 |
| Huafeng Liu | 5 | 242 | 41.00 |
| Quanzheng Li | 6 | 181 | 32.36 |