FFU-Net: Feature Fusion U-Net for Lesion Segmentation of Diabetic Retinopathy

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/bmri/volume-2021/6644071/figures/6644071.fig.004a.svgz" name="6644071.fig.004a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Lesions of diabetic retinopathy</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/bmri/volume-2021/6644071/figures/6644071.fig.004b.svgz" name="6644071.fig.004b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Positive samples</td></tr><tr class="fig-image" id="c"><td><object data="https://static-preview.hindawi.com/articles/bmri/volume-2021/6644071/figures/6644071.fig.004c.svgz" name="6644071.fig.004c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Negative samples</td></tr></table>

<div>Color fundus samples of dataset IDRID: (a) the sample contains microaneurysms, hard exudates, soft exudates, and hemorrhage; (b) positive samples; (c) negative samples.</div>

BioMed Research International

fig4

Figure 4

Figure 4: FFU-Net: Feature Fusion U-Net for Lesion Segmentation of Diabetic Retinopathy 