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©The Author(s) 2023.
World J Radiol. Dec 28, 2023; 15(12): 359-369
Published online Dec 28, 2023. doi: 10.4329/wjr.v15.i12.359
Published online Dec 28, 2023. doi: 10.4329/wjr.v15.i12.359
Table 4 Amount of time needed to annotate the tumor
| Lesion size | Annotation time based on technique (Min:Sec ± min) | ||||
| Manual (n = 3 each) | AI-single voter (n = 3 each) | AI-2-voter (n = 3 each) | Skip-1 (n = 3 each) | Skip-2 (n = 3 each) | |
| Large | 22:09 ± 0.18 | 21:00 ± 0.23 | 20:29 ± 0.22 | 8:58 ± 1.22 | 5:34 ± 1.19 |
| Medium | 15:06 ± 0.4 | 10:37 ± 0.25 | 9:13 ± 0.15 | 4:58 ± 2.57 | 1:14 ± 1.38 |
| Small | 5:54 ± 0.07 | 6:26 ± 0.03 | 5:44 ± 0.02 | 2:23 ± 0.14 | 1:24 ± 0.28 |
- Citation: Grudza M, Salinel B, Zeien S, Murphy M, Adkins J, Jensen CT, Bay C, Kodibagkar V, Koo P, Dragovich T, Choti MA, Kundranda M, Syeda-Mahmood T, Wang HZ, Chang J. Methods for improving colorectal cancer annotation efficiency for artificial intelligence-observer training. World J Radiol 2023; 15(12): 359-369
- URL: https://www.wjgnet.com/1949-8470/full/v15/i12/359.htm
- DOI: https://dx.doi.org/10.4329/wjr.v15.i12.359