Titlebook: Ophthalmic Medical Image Analysis; 9th International Wo Bhavna Antony,Huazhu Fu,Yalin Zheng Conference proceedings 2022 The Editor(s) (if a

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,Multimodal Information Fusion for?Glaucoma and?Diabetic Retinopathy Classification,and diabetic retinopathy classification, using the public GAMMA dataset (fundus photographs and OCT) and a private dataset of PLEX?Elite 9000 (Carl Zeis Meditec Inc.) OCT angiography acquisitions, respectively. Our hierarchical fusion method performed the best in both cases and paved the way for bet

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,Mapping the?Ocular Surface from?Monocular Videos with?an?Application to?Dry Eye Disease Grading,shape of the eye, through semantic segmentation as well as sphere fitting. The achieved tracking errors outperform the state-of-the-art, with a mean Euclidean distance as low as 0.48% of the image width on our test set. This registration improves the DED severity classification by a 0.20 AUC differe

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Intra-operative OCT (iOCT) Super Resolution: A Two-Stage Methodology Leveraging High Quality Pre-oparn the super-resolution mapping. Quantitative analysis using both full-reference and no-reference image quality metrics demonstrates that our approach clearly outperforms the learning-based state-of-the art techniques with statistical significance. Achieving iOCT image quality comparable to preOCT

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,Domain Adaptive Retinal Vessel Segmentation Guided by?High-frequency Component, discrepancy between the source domain and target domain retinal images. After that, images produced by the two modules are fed into a multi-input deep segmentation model, and the full utilization of features from different modalities is ensured by the deep supervision mechanism. Experiments prove t

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,Tiny-Lesion Segmentation in?OCT via?Multi-scale Wavelet Enhanced Transformer, interpretability while avoiding feature loss, and further enhancing the ability of the network to represent local detailed features. Meanwhile, we also develop a novel multi-scale transformer module to further improve the model’s capacity of extracting the multi-scale long-dependent global features