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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: IEEE Trans Med Imaging. 2020 Nov 30;39(12):4071–4084. doi: 10.1109/TMI.2020.3011626

TABLE V.

Impact of using segmentation probability maps for adversarial training on segmentation accuracy.

T1wFS MR Parotid (N = 77) T1w SPIR MR Abdomen (N = 10)
Discriminator Parotid right Parotid left Avg. Liver Spleen Kidney left Kidney right Avg.
i. Multi-channel segmentation prob 0.74±0.07 0.73±0.06 0.74 0.89±0.02 0.84±0.05 0.79±0.12 0.80±0.07 0.83
ii. Aggregated segmentation prob 0.75±0.05 0.75±0.06 0.75 0.89±0.03 0.83±0.09 0.80±0.11 0.81±0.09 0.83
iii. Multi-channel segmentation prob + Image 0.78±0.05 0.77±0.05 0.78 0.90±0.03 0.85±0.05 0.80±0.10 0.82±0.07 0.84
iv. SOI-specific segmentation prob + Image 0.79±0.03 0.78±0.04 0.79 0.91±0.02 0.85±0.08 0.81±0.10 0.82±0.07 0.85
v. Aggregated segmentation prob + Image 0.82±0.03 0.81±0.05 0.82 0.92±0.02 0.87±0.03 0.83±0.10 0.84±0.06 0.87