MedFLIP: Medical Vision-and-Language Self-supervised Fast Pre-Training with Masked Autoencoder

arXiv:2403.04626v1 Announce Type: cross
Abstract: Within the domain of medical analysis, extensive research has explored the potential of mutual learning between Masked Autoencoders(MAEs) and multimodal data. However, the impact of MAEs on intermodality remains a key challenge. We introduce MedFLIP, a Fast Language-Image Pre-training method for Medical analysis. We explore MAEs for zero-shot learning with crossed domains, which enhances the model ability to learn from limited data, a common scenario in medical diagnostics. We verify that masking an image does …

abstract analysis arxiv autoencoder autoencoders challenge cs.cl cs.cv cs.lg data domain eess.iv explore however image impact key language masked autoencoder medical multimodal multimodal data pre-training research training type vision vision-and-language