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cs.CV2024
IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
Anurag Shandilya, Swapnil Bhat, Akshat Gautam +4
Generative models have proven to be very effective in generating synthetic medical images and find applications in downstream tasks such as enhancing rare disease datasets, long-ta…
cs.CV2024★ 1 cited
INSITE: labelling medical images using submodular functions and semi-supervised data programming
Akshat Gautam, Anurag Shandilya, Akshit Srivastava +3
The necessity of large amounts of labeled data to train deep models, especially in medical imaging creates an implementation bottleneck in resource-constrained settings. In Insite…