PairAug: What Can Augmented Image-Text Pairs Do for Radiology?

arXiv:2404.04960v1 Announce Type: new
Abstract: Current vision-language pre-training (VLP) methodologies predominantly depend on paired image-text datasets, a resource that is challenging to acquire in radiology due to privacy considerations and labelling complexities. Data augmentation provides a practical solution to overcome the issue of data scarcity, however, most augmentation methods exhibit a limited focus, prioritising either image or text augmentation exclusively. Acknowledging this limitation, our objective is to devise a framework capable of concurrently augmenting medical image and text data. We …

arxiv cs.cv image radiology text type