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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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11#
發(fā)表于 2025-3-23 09:51:59 | 只看該作者
,Mapping the?Ocular Surface from?Monocular Videos with?an?Application to?Dry Eye Disease Grading, of DED usually rely on ocular surface analysis through slit-lamp examinations. However, evaluations are subjective and non-reproducible. To improve the diagnosis, we propose to 1) track the ocular surface in 3-D using video recordings acquired during examinations, and 2) grade the severity using re
12#
發(fā)表于 2025-3-23 17:54:07 | 只看該作者
13#
發(fā)表于 2025-3-23 19:37:33 | 只看該作者
,Localizing Anatomical Landmarks in?Ocular Images Using Zoom-In Attentive Networks,ures. Their locations are elusive and easily confused with the background, and thus precise localization highly depends on the context formed by their surrounding areas. In addition, the required precision is usually higher than segmentation and object detection tasks. Therefore, localization has it
14#
發(fā)表于 2025-3-24 02:16:32 | 只看該作者
15#
發(fā)表于 2025-3-24 04:54:51 | 只看該作者
,Domain Adaptive Retinal Vessel Segmentation Guided by?High-frequency Component,tion algorithm has become one of the research hotspots in the field of medical image processing. However, there are still several unsolved difficulties in this task: the existed methods are too sensitive to the low-frequency noise in the fundus images, and there are few annotated data sets available
16#
發(fā)表于 2025-3-24 08:30:27 | 只看該作者
,Tiny-Lesion Segmentation in?OCT via?Multi-scale Wavelet Enhanced Transformer,allenge to accurately segment retinal lesions in OCT images. This is due to the complicated pathological features of retinal diseases, resulting in severe regional scale imbalance between different lesions, and leading to the problem of target tendency of the network during training, subsequently re
17#
發(fā)表于 2025-3-24 14:42:09 | 只看該作者
18#
發(fā)表于 2025-3-24 18:47:40 | 只看該作者
,Self-supervised Learning for?Anomaly Detection in?Fundus Image, should be well applied to medical data that are not seen. Focusing on a fact that an object photograph consists of reflectance and illumination information, we propose a new data augmentation method that can change illumination information for creating a new fundus image by preserving the reflectan
19#
發(fā)表于 2025-3-24 22:05:07 | 只看該作者
,GARDNet: Robust Multi-view Network for?Glaucoma Classification in?Color Fundus Images,iagnostics is carried out when one’s sight has already significantly degraded due to the lack of noticeable symptoms at early stage of the disease. Regular glaucoma screenings of the population shall improve early-stage detection, however the desirable frequency of etymological checkups is often not
20#
發(fā)表于 2025-3-25 01:39:49 | 只看該作者
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