Author Affiliations
1 College of Science, North University of China, Taiyuan, Shanxi 0 30051, China2 Shanxi Key Laboratory of Signal Capturing & Processing, North University of China, Taiyuan, Shanxi 0 30051, China;show less
Fig. 1. Three transformations apply to head model. (a) TV operator; (b) NLTV operator; (c) RE_NLTV operator
Fig. 2. Energy spectrum of 120 kVp simulated voltages
Fig. 3. Two-dimensional image of the simulation model
Fig. 4. Reference images used in RI_NLTV algorithm. (a) For chapter 3.1; (b) for chapter 3.2
Fig. 5. Reconstructions with different algorithms under high and low noise level. (a) TV algorithm; (b) NLTV algorithm; (c) RE_NLTV algorithm; (d) RI_NLTV algorithm
Fig. 6. Convergence of different algorithms under the low noise level
Fig. 7. Reconstructions with different algorithms underthree energy bins. (a) TV algorithm; (b) NLTV algorithm; (c) RE_NLTV algorithm; (d) RI_NLTV algorithm
Fig. 8. Reconstructions with different algorithms under high and low noise level in the mouse model. (a) TV algorithm; (b) NLTV algorithm; (c) RE_NLTV algorithm; (d) RI_NLTV algorithm
Object | Center /cm | Size /cm | Material |
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1 | (0.00,0.00) | (0.92,0.69) | Soft tissue | 2 | (0.20,0.20) | (0.03,0.03) | Air | 3 | (0.00,-0.10) | (0.05,0.05) | Blood | 4 | (0.00,0.50) | (0.20,0.08) | 0.3% Iodine+99.7% blood | 5 | (0.65,0.20) | (0.20,0.08) | 0.2% Kalium+99.8% blood | 6 | (0.45,-0.38) | (0.20,0.08) | 1% Barium+99% water | 7 | (-0.45,-0.38) | (0.20,0.08) | 0.3% Ferrum+99.7% blood | 8 | (-0.65,0.20) | (0.20,0.08) | 10% Calcium+90% water |
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Table 1. Position and size of the corresponding material in the model
Item | Low noise level | High noise level | |
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TV | | NLTV | RE_NLTV | RI_NLTV | TV | NLTV | RE_NLTV | RI_NLTV |
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SNR | 19.3845 | 18.1667 | 18.4086 | 21.1183 | 17.3146 | 17.1100 | 17.2012 | 19.9054 | MSE | 8.62×10-5 | 1.14×10-4 | 1.07×10-4 | 5.78×10-5 | 1.39×10-4 | 1.46×10-4 | 1.42×10-4 | 7.64×10-4 | NMSD | 0.1073 | 0.1235 | 0.1201 | 0.0879 | 0.1362 | 0.1395 | 0.1380 | 0.1011 |
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Table 2. Evaluation parameters of reconstruction with different algorithms under high and low noise level
Algorithm | Bin1 | Bin2 | Bin3 |
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SNR | MSE | NMSD | SNR | MSE | NMSD | SNR | MSE | NMSD |
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TV | 17.40 | 0.0011 | 0.1348 | 17.71 | 2.62×10-4 | 0.1302 | 17.64 | 3.06×10-4 | 0.1312 | NLTV | 16.57 | 0.0014 | 0.1484 | 16.80 | 3.22×10-4 | 0.1444 | 16.79 | 3.73×10-4 | 0.1448 | RE_NLTV | 17.06 | 0.0012 | 0.1403 | 17.12 | 3.00×10-4 | 0.1393 | 17.09 | 3.48×10-4 | 0.1398 | RI_NLTV | 17.64 | 0.0011 | 0.1312 | 18.19 | 2.70×10-4 | 0.1232 | 18.37 | 2.25×10-4 | 0.1207 |
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Table 3. Evaluation parameter of different algorithms under three energy bins
Item | Low noise level | High noise level |
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TV | NLTV | RE_NLTV | RI_NLTV | TV | NLTV | RE_NLTV | RI_NLTV |
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SNR | 16.4527 | 16.5221 | 16.6073 | 17.2900 | 16.4309 | 16.3803 | 16.4572 | 17.3558 | MSE | 6.17×10-4 | 5.20×10-4 | 5.10×10-4 | 4.36×10-5 | 5.31×10-4 | 5.37×10-4 | 5.28×10-4 | 4.29×10-4 | NMSD | 0.1504 | 0.1492 | 0.1478 | 0.1366 | 0.1508 | 0.1517 | 0.1504 | 0.1356 |
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Table 4. Evaluation parameters of reconstruction with different algorithms under high and low noise level