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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: Int J Comput Assist Radiol Surg. 2022 Sep 24;18(3):449–460. doi: 10.1007/s11548-022-02757-2

Table 1.

Training result of 3D U-Net using automatic segmentation of prostate and extracapsular structures method.

Data split; training / validation / test, n Loss coefficient Dice score

Prostate 58 / 10 / 5 0.10 0.83
Rectum 58 / 10 / 5 0.15 0.76
Bladder 58 / 10 / 5 0.22 0.81
Bulb of penis 58 / 10 / 5 0.14 0.82
Bulbospongiosus muscle 48 / 5 / 3 0.17 0.44
Crus of penis 58 / 10 / 5 0.10 0.84
Obturator internus muscle 58 / 10 / 5 0.10 0.84
Pelvic diaphragm muscle 58 / 10 / 5 0.10 0.60
Transverse perineal muscle 58 / 10 / 5 0.2 0.15
Ischiocavern muscle 58 / 10 / 5 0.17 0.55
Pubis bone 58 / 10 / 5 0.10 0.73
Seminal Vesicle 58 / 10 / 5 0.2 0.43