Diffusion based Zero-shot Medical Image-to-Image Translation for Cross Modality Segmentation

arXiv:2404.01102v1 Announce Type: cross
Abstract: Cross-modality image segmentation aims to segment the target modalities using a method designed in the source modality. Deep generative models can translate the target modality images into the source modality, thus enabling cross-modality segmentation. However, a vast body of existing cross-modality image translation methods relies on supervised learning. In this work, we aim to address the challenge of zero-shot learning-based image translation tasks (extreme scenarios in the target modality is unseen in the training phase). …

abstract arxiv cs.cv cs.lg deep generative models diffusion eess.iv enabling generative generative models however image images image-to-image image-to-image translation medical segment segmentation translate translation type vast zero-shot