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. Author manuscript; available in PMC: 2025 Sep 1.
Published in final edited form as: Pattern Recognit. 2024 Apr 11;153:110494. doi: 10.1016/j.patcog.2024.110494

Table 2:

Summary of image set and nnU-Net hyperparameters used for training and test the approaches described in the study. For approach IV, D is determined from the optimal plane spacing. Phantoms simulated using 0.1% of fraction of dense compartments were excluded from the test sets.

Approach I II III IV
nnU-Net Step Training/Testing Training /Testing Fine-tuning/Testing Training/Testing
Phantoms (#)
Per Fraction of Dense Comp. (0.1, 10, 20, 30, and 50%)
1,000/260

200/65
−/260

−/65
750/260

150/65
1,000/260

200/65
nnU-Net Models (#) 3 0 2 1
Volume (w×h×d) 97×256×51 97×256×51 97×256×51 97×256×D
Epochs (#) 60 - 60 60
Batch Size (#) 6 - 6 6