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Table 4 The model segmentation results with and without Multi input, deeper network and post-processing

From: Joint optic disc and cup segmentation based on densely connected depthwise separable convolution deep network

Method

DRISHTI-GS dataset

REFUGE dataset

\(DC_{disc}\,(mean)\)

\(DC_{cup}\,(mean)\)

\(DC_{disc}\,(mean)\)

\(DC_{cup}\,(mean)\)

Without image pyramid input

0.9743

0.9076

0.9589

0.8880

Without multi-DDSC blocks

0.9746

0.8939

0.9575

0.8837

DDSC-Net

0.9779

0.9123

0.9592

0.8894

DDSC-NET + post-processing

0.9780

0.9123

0.9601

0.8903

  1. Italics indicate the best results
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BMC Medical Imaging

ISSN: 1471-2342

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