Abstract: We identify two major limitations in the existing studies on retinal vessel segmentation: (1) Most existing works are restricted to one modality, i.e., the Color Fundus (CF). However, ...

I'm not familiar with core dump analysis, and the core dump is too big to upload. I asked AI to analyze the core dump, and the following are its results (Just tell me if you need other information): ...

Abstract: Retinal image segmentation is essential for analyzing retinal structures like vessels and diagnosing retinopathy. However, the inherent intricacy of the retina, along with annotation ...

Daniela Ferrara, MD, PhD, FASRS, Chief Medical Officer at TopCon Healthcare and retina specialist, discussed AI's transformative role in ophthalmology. She moderated a panel at the OIS Retina event ...

This conversation features Daniella Ferrara, Chief Medical Officer for TopCon Healthcare, discussing the transformative potential of artificial intelligence in retinal imaging and ophthalmology.

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Introduction: The retinal microvasculature has been definitively linked to a variety of diseases, such as ophthalmological, cardiovascular, and other medical conditions. Precisely identifying the ...

Using any torch.compile after PyTorch 2.8.0 (and 2.9 nightlies) results in Segmentation fault with Intel ARC A770 / XPU Provided code and more complex torch.compile works fine with PyTorch 2.7.1+xpu, ...

Segmentations of retinal optical coherence tomography (OCT) images provide valuable information about each specific retinal layer. However, processing images from degenerative retina remains ...

Researchers introduce a multistage dual-branch network to improve accuracy and efficiency. A novel optical coherence tomography (OCT) retinal geographic atrophy (GA) segmentation method has been ...