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RetinaRegNet: A zero-shot approach for retinal image registration.

Comput Biol Med

January 2025

Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, 32610, United States; Department of Medicine, University of Florida, Gainesville, FL, 32610, United States; Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, 32610, United States; Intelligent Clinical Care Center, University of Florida, Gainesville, FL, 32610, United States. Electronic address:

Retinal image registration is essential for monitoring eye diseases and planning treatments, yet it remains challenging due to large deformations, minimal overlap, and varying image quality. To address these challenges, we propose RetinaRegNet, a multi-stage image registration model with zero-shot generalizability across multiple retinal imaging modalities. RetinaRegNet begins by extracting image features using a pretrained latent diffusion model.

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Purpose: Chronic inflammation plays an important role in the pathogenesis of choroidal neovascularization (CNV). This study aimed to investigate the effect of the CHF5074, a γ-secretase inhibitor, on angiogenesis in a laser-induced CNV model and elucidate its possible molecular mechanism.

Methods: Male C57/BL6J mice aged between 6 to 8 weeks were employed to set up a laser-induced model of CNV.

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Background: Inadequate bowel perfusion is among risk factors for colorectal anastomotic leaks. Perfusion can be assessed with indocyanine green fluorescence angiography (ICG) during colon resections. Possible benefits from its systematic use in high-risk patients with rectal cancer remain inconsistent.

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Background: This study aimed to identify the clinical characteristics of cases that is related to the response rate of adalimumab (ADA) treatment.

Methods: A retrospective review of medical records was conducted for pediatric patients with non-infectious uveitis undergoing ADA treatment for a minimum of six months. The patients were stratified into two groups: those with anterior segment inflammation (ASI+) and those without anterior segment inflammation (ASI-).

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