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Visual Computing for Industry, Biomedicine, and Art
Fig. 5 | Visual Computing for Industry, Biomedicine, and Art

Fig. 5

From: Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning

Fig. 5

A typical example of automatic superficial foveal avascular zone segmentation. The dice similarity coefficientwas 0.990. a Optical coherence tomography angiography (OCTA) image; b Automatic segmentation result (blue area) presented on OCTA image; c Ground truth (GT) (red area) presented on OCTA image; d Magnification of the differences between automatic segmentation results (blue area) and GT (red area); the purple area is the overlapping part of the automatic segmentation results and the GT

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