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Metabolic Fingerprint of Dual Body Fluids Deciphers Diabetic Retinopathy.

Small

January 2025

Department of Ophthalmology, National Clinical Research Center for Eye Diseases, Shanghai Gene Therapy Center, Shanghai Key Laboratory of Ocular Fundus Disease, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200040, P. R. China.

Diabetic retinopathy (DR) is a microvascular complication of diabetes, affecting 34.6% of diabetes patients worldwide. Early detection and timely treatment can effectively improve the prognosis of DR.

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Background: The aim of the study was to investigate the quantitative differences between severe stage 3 and stage 4A retinopathy of prematurity (ROP) by evaluating the pre-treatment fundus photographs.

Methods: Thirty-three eyes with clinical diagnosed as severe stage 3 were classified as severe stage 3 group. Twenty-two eyes with retinal detachment without foveal involvement were classified as stage 4A group.

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Magnetic resonance imaging (MRI) is frequently used to monitor disease progression in multiple sclerosis (MS). This study aims to systematically evaluate the correlation between MRI measures and histopathological changes, including demyelination, axonal loss, and gliosis, in the central nervous system of MS patients. We systematically reviewed post-mortem histological studies evaluating myelin density, axonal loss, and gliosis using quantitative imaging in MS.

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Multi scale multi attention network for blood vessel segmentation in fundus images.

Sci Rep

January 2025

Department of Data Science and Artificial Intelligence, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.

Precise segmentation of retinal vasculature is crucial for the early detection, diagnosis, and treatment of vision-threatening ailments. However, this task is challenging due to limited contextual information, variations in vessel thicknesses, the complexity of vessel structures, and the potential for confusion with lesions. In this paper, we introduce a novel approach, the MSMA Net model, which overcomes these challenges by replacing traditional convolution blocks and skip connections with an improved multi-scale squeeze and excitation block (MSSE Block) and Bottleneck residual paths (B-Res paths) with spatial attention blocks (SAB).

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