Titlebook: Ophthalmic Medical Image Analysis; 6th International Wo Huazhu Fu,Mona K. Garvin,Yalin Zheng Conference proceedings 2019 Springer Nature Sw

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Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Reng. Evaluating photoreceptor cell morphology in retinal diseases is important for monitoring the onset and progression of blindness, but segmentation of these cells is a critical first step. Most segmentation approaches focus on cell region extraction, without directly considering cell boundary loca

palliate

Robust Optic Disc Localization by Large Scale Learning, diseases. Many studies have been done for the automatic localization of OD but not reach a perfect performance yet. The bottleneck is lack of data and corresponding models that can handle with such big data. In this paper, we proposed an automatic OD localization method based on the hourglass netwo

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The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection,first boundary in the OCT, which can help to extract the retinal pigment epithelium (RPE) through gradient edge information to locate the boundary of the optic disc. Thus, the ILM layer segmentation is of great importance for optic disc localization. In this paper, we build a new optic disc centered

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Fundus Image Based Retinal Vessel Segmentation Utilizing a Fast and Accurate Fully Convolutional Neascular diseases, for which a prerequisite is to segment out the retinal vessels. The relatively low contrast of retinal vessels and the presence of various types of lesions such as hemorrhages and exudate nevertheless make this task challenging. In this paper, we proposed and validated a novel reti

PACT

Network Pruning for OCT Image Classification, neural network makes CNN models computationally expensive. This leads to slow inference speed, especially for 3D data such as optical coherence tomography (OCT) for retinal images. A volume OCT scan of retina often contains hundreds of 2D images which needs to be analyzed sequentially in a local co

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Multi-discriminator Generative Adversarial Networks for Improved Thin Retinal Vessel Segmentation, thin vessels make accurate segmentation of the thin vasculature extremely challenging. In this paper, we present a novel multiscale segmentation method named Multiple discriminator generative adversarial network (MuGAN). MuGAN contains multiple discriminators with different effective receptive fiel

Stagger

Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior,oveal center determines the severity degree of visual impacts. Therefore, accurate fovea localization is the basis of the computer-aided ophthalmic diagnosis and vision screening. A simple but effective fovea localization algorithm based on the Faster R-CNN and physiological structure prior is prese

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