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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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Background: Disparities in labor epidural analgesia (LEA) management could reduce maternal satisfaction and increase risk. We compared times from the first administration of breakthrough pain medication (top-up) to LEA replacement to evaluate disparities across race.

Methods: In this retrospective cohort study (01-01-2018 to 12-31-2022), all patients with LEA and maternal race/ethnicity of non-Hispanic White or Black were eligible.

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Context: With the advent of the Single Accreditation System (SAS) within the Accreditation Council for Graduate Medical Education (ACGME), few programs have achieved Osteopathic Recognition (OR) status to date. OR is an accreditation that graduate medical education (GME) programs can achieve to distinctly acknowledge the additional focus on osteopathic training. There is an effort by national osteopathic organizations to determine barriers for programs to achieve OR and what innovative methods might help overcome them.

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Background: Although existing disease preparedness and response frameworks provide guidance about strengthening emergency response capacity, little attention is paid to health service continuity during emergency responses. During the 2014 Ebola outbreak, there were 11,325 reported deaths due to the Ebola virus and yet disruption in access to care caused more than 10,000 additional deaths due to measles, HIV/AIDS, tuberculosis, and malaria. Low- and middle-income countries account for the largest disease burden due to HIV, tuberculosis, and malaria and yet previous responses to health emergencies showed that HIV, tuberculosis, and malaria service delivery can be significantly disrupted.

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Background: Monitoring vital signs in hospitalized patients is crucial for evaluating their clinical condition. While early warning scores like the modified early warning score (MEWS) are typically calculated 3 to 4 times daily through spot checks, they might not promptly identify early deterioration. Leveraging technologies that provide continuous monitoring of vital signs, combined with an early warning system, has the potential to identify clinical deterioration sooner.

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