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Realistic in Generation of HEp-2 Cell Images Using Latent Diffusion Models: a Multi-center Visual Turing Test
Sponsor: Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
Summary
The objective of this prospective observational study is to rigorously examine the feasibility and efficacy of utilizing latent diffusion models for data augmentation in anti-nuclear antibody (ANA) Hep-2 cell immunofluorescence images. The main question it aims to answer is: Can the application of such models potentially enhance the data quality, increase sample diversity, or improve the accuracy and efficiency of subsequent analytical processes (like disease diagnosis and classification) when utilized with ANA-related images?
Official title: Evaluating the Realism of ANA HEp-2 Cell Images Synthesized Using Latent Diffusion Models: A Multi-center Visual Turing Test
Key Details
Gender
All
Age Range
Any - Any
Study Type
OBSERVATIONAL
Enrollment
300
Start Date
2024-09
Completion Date
2026-06
Last Updated
2024-08-07
Healthy Volunteers
Yes
Interventions
referring to the results of AI model output
determining the ANA pattern type with or without referring to the results of AI model output.