Name
Title | ||
|---|---|---|
Image segmentation and activity estimation for microPET C-raclopride images using an expectation-maximum algorithm with a mixture of Poisson distributions. |
Abstract | ||
|---|---|---|
The objective of this study was to use a mixture of Poisson (MOP) model expectation maximum (EM) algorithm for segmenting microPET images. Simulated rat phantoms with partial volume effect and different noise levels were generated to evaluate the performance of the method. The partial volume correction was performed using an EM deblurring method before the segmentation. The EM–MOP outperforms the EM–MOP in terms of the estimated spatial accuracy, quantitative accuracy, robustness and computing efficiency. To conclude, the proposed EM–MOP method is a reliable and accurate approach for estimating uptake levels and spatial distributions across target tissues in microPET 11C-raclopride imaging studies. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.compmedimag.2011.01.004 | Computerized Medical Imaging and Graphics |
Keywords | Field | DocType |
PET,Image segmentation,Expectation maximum (EM) algorithm,Mixture of Poisson (MOP),Mixture of Gaussian (MOG) | Deblurring,Pattern recognition,Segmentation,Raclopride,Algorithm,Robustness (computer science),Image segmentation,Artificial intelligence,Poisson distribution,Partial volume correction,Partial volume,Mathematics | Journal |
Volume | Issue | ISSN |
35 | 5 | 0895-6111 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kuan-Hao Su | 1 | 24 | 5.46 |
| Jay S Chen | 2 | 161 | 16.23 |
| Jih-Shian Lee | 3 | 3 | 2.17 |
| Chi-Min Hu | 4 | 0 | 0.34 |
| Chi-Wei Chang | 5 | 7 | 0.85 |
| Yuan-Hwa Chou | 6 | 4 | 1.88 |
| Ren-Shyan Liu | 7 | 0 | 0.34 |
| Jyh-Cheng Chen | 8 | 8 | 3.60 |