I-DiPT adapts a frozen medical image classifier to test images arriving in random domain fragments using image-level disentangled prompts, masked consistency, and graph distillation of historical prompts.
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F^2TTA: Free-Form Test-Time Adaptation on Cross-Domain Medical Image Classification via Image-Level Disentangled Prompt Tuning
I-DiPT adapts a frozen medical image classifier to test images arriving in random domain fragments using image-level disentangled prompts, masked consistency, and graph distillation of historical prompts.