Table 6 Validation results for two models from the DS and DNS pipelines, both using input images of size 512\(\times\)512\(\times\)64 and Z-Score pixel intensity normalization, with pixel spacing normalization applied in the DS model.

From: The impact of pre-processing techniques on deep learning breast image segmentation

 

DSC

HD (in mm)

Model name

Total

Breast

FGT

Vessels

Total

Breast

FGT

Vessels

DS 512 Spacing Z-Score

0.693 ± 0.018

0.919

0.835

0.324

98 ± 11.3

127

75

90

DNS 512 Z-Score

0.701 ± 0.018

0.923

0.834

0.346

106 ± 13

145

84

90

Terminology

Pipeline

Orientation

Pixel spacing

Pixel intensity

Resize

DS 512 Spacing Z-Score

DS

No

Yes

Z-Score

512 × 512 × 64

DNS 512 Z-Score

DNS

No

No

Z-Score

512 × 512 × 64

  1. The first part of the table reports the mean DSC ± standard deviation and HD ± standard deviation over 5-fold cross-validation on the Duke-Breast-Cancer-MRI dataset, showing both the overall averages (Total) and values for each label (Breast, FGT, Vessels). The second part of the table provides a legend describing the model names.
  2. Bold values denote the best Total results.
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