Titlebook: Ophthalmic Medical Image Analysis; 10th International W Bhavna Antony,Hao Chen,Yalin Zheng Conference proceedings 2023 The Editor(s) (if ap

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,Recurrent Self Fusion: Iterative Denoising for?Consistent Retinal OCT Segmentation, on both a Spectralis and Cirrus OCT device are used for validation. The results demonstrate that the RSF algorithm effectively reduces speckle contrast and enhances the consistency of retinal OCT segmentation.

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,UAU-Net: United Attention U-Shaped Network for?the?Segmentation of?Pigment Deposits in?Fundus Imageent deposits, and the SEAM is proposed to preserve detailed features and enhance the model’s ability to segment small targets. Comprehensive experiments on 215 fundus images show that UAU-Net outperforms other state-of-the-art methods with Dice and Intersection-over-Union of 60.25% and 44.91%, respectively.

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,Adapting Segment Anything Model (SAM) for?Retinal OCT,d established methods in some circumstances. The findings highlight SAM’s adaptability and robustness, showcasing its utility as a valuable tool in retinal OCT image analysis and paving the way for further advancements in this domain.

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/o/image/702388.jpg

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https://doi.org/10.1007/978-3-031-44013-7Computer Science; Computer-aided detection; ophthalmic imaging; medical image analysis; machine learning

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978-3-031-44012-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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