Results 101 to 110 of about 277,755 (206)

Direct observation and measurement of circumlental space and its relation to anterior chamber angle characteristics in iridotomized phakic eyes with primary angle closure disease

open access: yesScientific Reports
Primary angle closure disease (PACD) is a major cause of blindness worldwide. It has a high prevalence in East Asia, especially in China, which leads to a higher incidence of blindness than open-angle glaucoma.
Zhiqiao Liang   +8 more
doaj   +1 more source

Automated Retinal Image Analysis and Medical Report Generation through Deep Learning [PDF]

open access: yesarXiv
The increasing prevalence of retinal diseases poses a significant challenge to the healthcare system, as the demand for ophthalmologists surpasses the available workforce. This imbalance creates a bottleneck in diagnosis and treatment, potentially delaying critical care.
arxiv  

RetinalGPT: A Retinal Clinical Preference Conversational Assistant Powered by Large Vision-Language Models [PDF]

open access: yesarXiv
Recently, Multimodal Large Language Models (MLLMs) have gained significant attention for their remarkable ability to process and analyze non-textual data, such as images, videos, and audio. Notably, several adaptations of general-domain MLLMs to the medical field have been explored, including LLaVA-Med.
arxiv  

CUNSB-RFIE: Context-aware Unpaired Neural Schrödinger Bridge in Retinal Fundus Image Enhancement [PDF]

open access: yesarXiv
Retinal fundus photography is significant in diagnosing and monitoring retinal diseases. However, systemic imperfections and operator/patient-related factors can hinder the acquisition of high-quality retinal images. Previous efforts in retinal image enhancement primarily relied on GANs, which are limited by the trade-off between training stability and
arxiv  

Cellular autoimmunity to retinal specific antigens in patients with Behcet's disease. [PDF]

open access: bronze, 1993
Joyce Hisae Yamamoto   +4 more
openalex   +1 more source

Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models [PDF]

open access: yesarXiv
Recent advancements in deep learning have shown significant potential for classifying retinal diseases using color fundus images. However, existing works predominantly rely exclusively on image data, lack interpretability in their diagnostic decisions, and treat medical professionals primarily as annotators for ground truth labeling.
arxiv  

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