General Purpose Image Encoder DINOv2 for Medical Image Registration

arXiv:2402.15687v1 Announce Type: new
Abstract: Existing medical image registration algorithms rely on either dataset specific training or local texture-based features to align images. The former cannot be reliably implemented without large modality-specific training datasets, while the latter lacks global semantics thus could be easily trapped at local minima. In this paper, we present a training-free deformable image registration method, DINO-Reg, leveraging a general purpose image encoder DINOv2 for image feature extraction. The DINOv2 encoder was trained using the ImageNet data …

abstract algorithms arxiv cs.ai cs.cv dataset datasets encoder features general global image images medical paper registration semantics texture training training datasets type