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Table 5 A summary of data employed to perform single-view segmentation model together with information on the training process

From: A fully automated deep learning pipeline for micro-CT-imaging-based densitometry of lung fibrosis murine models

Single-view models summary on single class (lungs)

 

Number of train µCT

Number of test µCT

Image dimension

Number of epochs

Training time [h]

Binarization threshold

Lung DSC on test set

Axial

195 (74,880 2D slices)

14 (3376 2D slices)

(192, 120)

4

05:49:37

0.55

0.943 ± 0.038

Sagittal

195 (37,440 2D slices)

14 (2688 2D slices)

(192, 192)

10

06:52:29

0.55

0.934 ± 0.055

Coronal

195 (31,200 2D slices)

14 (2240 2D slices)

(192, 120)

9

06:37:13

0.5

0.943 ± 0.037