Papers › Optic Disc, Cup and Fovea Detection from Retinal Images Using U-Net++ with EfficientNet Encoder

Optic Disc, Cup and Fovea Detection from Retinal Images Using U-Net++ with EfficientNet Encoder

20 Nov 2020archive 2025-07-28

Ravi Kamble, Pranab Samanta, Nitin Singhal

The accurate detection of retinal structures like an optic disc (OD), cup, and fovea is crucial for the analysis of Age-related Macular Degeneration (AMD), Glaucoma, and other retinal conditions. Most segmentation methods rely on separate detection of these retinal structures due to which a combined analysis for computer-aided ophthalmic diagnosis and screening is challenging. To address this issue, the paper introduces an approach incorporating OD, cup, and fovea analysis together. The paper presents a novel method for the detection of OD with a cup and fovea using modified U-Net++ architecture with the EfficientNet-B4 model as a backbone. The extracted features from the EfficientNet are utilized using skip connections in U-Net++ for precise segmentation. Datasets from ADAM and REFUGE challenges are used for evaluating the performance. The proposed method achieved a success rate of 94.74% and 95.73% dice value for OD segmentation on ADAM and REFUGE data, respectively. For fovea detection, the average Euclidean distance of 26.17 pixels is achieved for the ADAM dataset. The proposed method stood first for OD detection and segmentation tasks in ISBI ADAM 2020 challenge.

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Tasks

Fovea Detection Optic Cup Detection Optic Cup Segmentation Optic Disc Detection Optic Disc Segmentation Segmentation

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Fovea Detection	REFUGE Challenge	EfficientNet+U-Net++	Euclidean Distance (ED)	35.18	#1 of 1	Archive leaderboard	report
Optic Cup Detection	REFUGE Challenge	EfficientNet+U-Net++	IoU	0.8128	#1 of 1	Archive leaderboard	report
Optic Cup Segmentation	REFUGE Challenge	EfficientNet+U-Net++	Dice	0.8762	#1 of 2	Archive leaderboard	report
Optic Disc Detection	REFUGE Challenge	EfficientNet+U-Net++	IoU	0.8847	#1 of 1	Archive leaderboard	report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

1x1 Convolution Adam Average Pooling Batch Normalization Convolution Dense Connections Depthwise Convolution Depthwise Separable Convolution Dropout EfficientNet Inverted Residual Block Pointwise Convolution RMSProp ReLU Sigmoid Activation Squeeze-and-Excitation Block

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