首创精神 发表于 2025-3-26 23:55:11
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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 betFlu表流动 发表于 2025-3-27 16:44:03
,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制造 发表于 2025-3-27 19:03:09
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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清楚 发表于 2025-3-28 07:02:25
,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微不足道 发表于 2025-3-28 12:40:53
,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