Which images to label for few-shot medical landmark detection?

arXiv:2112.04386v3 Announce Type: replace-cross
Abstract: The success of deep learning methods relies on the availability of well-labeled large-scale datasets. However, for medical images, annotating such abundant training data often requires experienced radiologists and consumes their limited time. Few-shot learning is developed to alleviate this burden, which achieves competitive performances with only several labeled data. However, a crucial yet previously overlooked problem in few-shot learning is about the selection of template images for annotation before learning, which affects the final performance. …

abstract arxiv availability cs.cv cs.lg data datasets deep learning detection eess.iv few-shot few-shot learning however images landmark medical performances scale success training training data type