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Table 5 Performance comparison of several nuclei segmentation methods and our nuclei segmentation method evaluated on the breast cancer histopathology image dataset (BNS)

From: An automatic nuclei segmentation method based on deep convolutional neural networks for histopathology images

Methods

Precision

Recall

F1-Score

ADC

AJI

PANGNET [18]

0.814

0.655

0.676

N/A

N/A

FCN [18]

0.823

0.752

0.763

N/A

N/A

DeconvNet [37]

0.864

0.773

0.805

N/A

N/A

Ensemble [19]

0.741

0.900

0.802

N/A

N/A

NB [22]

0.920

0.784

0.840

0.830

N/A

NucSeg

0.907

0.923

0.913

0.835

0.686

NucSeg-N

0.910

0.910

0.909

0.838

0.688

NucSeg-P

0.893

0.886

0.887

0.810

0.654

NucSeg-NP

0.912

0.889

0.899

0.818

0.665

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BMC Biomedical Engineering

ISSN: 2524-4426

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