Residues in Succession U-Net for Fast and Efficient Segmentation

Aqsa Sultana; Vijayan K. Asari; Theus Aspiras

doi:10.1117/12.2634286

13 June 2022 Residues in Succession U-Net for Fast and Efficient Segmentation

Aqsa Sultana, Vijayan K. Asari, Theus Aspiras

Proceedings Volume PC12101, Pattern Recognition and Tracking XXXIII; PC1210107 (2022) https://doi.org/10.1117/12.2634286
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

We propose a modified U-Net architecture incorporating the residues from successive layers for the extraction of features in subsequent layers. The new Residues in Succession U-Net model is evaluated for blood vessel segmentation in retinal images on a benchmark expert-annotated dataset viz. Structured Analysis of Retina (STARE). The testing and evaluation results shows improved performance when compared to U-Net and R2U-Net in the same experimentation setup. A nonlinear image enhancement strategy is employed to improve the fine details in the images so that the network will be able to capture more information in further processing.

Conference Presentation

Citation Download Citation

Aqsa Sultana, Vijayan K. Asari, and Theus Aspiras "Residues in Succession U-Net for Fast and Efficient Segmentation", Proc. SPIE PC12101, Pattern Recognition and Tracking XXXIII, PC1210107 (13 June 2022); https://doi.org/10.1117/12.2634286

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