Copyright
©The Author(s) 2020.
World J Gastroenterol. Sep 14, 2020; 26(34): 5156-5168
Published online Sep 14, 2020. doi: 10.3748/wjg.v26.i34.5156
Published online Sep 14, 2020. doi: 10.3748/wjg.v26.i34.5156
CT phase | Number of patients | Number of images | |||||||||
Without cancer cancer | With cancer | Total | Without cancer | With cancer | Total | ||||||
At tail1 | At head | Total | At tail | At head | Total | ||||||
Sets | Plain Scan | 182 | 91 | 123 | 214 | 396 | 1182 | 416 | 496 | 912 | 2094 |
Arterial phase | 179 | 91 | 129 | 220 | 399 | 1282 | 575 | 735 | 1310 | 2592 | |
Venous phase | 178 | 93 | 129 | 222 | 400 | 1287 | 573 | 699 | 1272 | 2559 | |
Total | 539 | 275 | 381 | 656 | 1195 | 3751 | 1564 | 1930 | 3494 | 7245 |
- Citation: Ma H, Liu ZX, Zhang JJ, Wu FT, Xu CF, Shen Z, Yu CH, Li YM. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis. World J Gastroenterol 2020; 26(34): 5156-5168
- URL: https://www.wjgnet.com/1007-9327/full/v26/i34/5156.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i34.5156