Representational convergence among medical image encoders is modest, driven mainly by the self-supervised pretraining objective rather than clinical supervision or scale, yet still sufficient for cross-encoder and cross-site classifier transfer.
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20
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Self-supervision drives representational convergence in medical foundation models more than clinical supervision
Representational convergence among medical image encoders is modest, driven mainly by the self-supervised pretraining objective rather than clinical supervision or scale, yet still sufficient for cross-encoder and cross-site classifier transfer.