Image Registration
Image registration aims to precisely align images from different sources or time points, a crucial preprocessing step for many medical and remote sensing applications. Current research emphasizes developing faster, more accurate, and robust registration methods, focusing on deep learning architectures like transformers and diffusion models, as well as incorporating probabilistic uncertainty quantification and techniques to handle multimodal data and complex deformations. These advancements are improving the accuracy and efficiency of various downstream tasks, including medical image analysis, surgical planning, and geospatial data integration.
Papers
Multi-modal deformable image registration using untrained neural networks
Quang Luong Nhat Nguyen, Ruiming Cao, Laura Waller
Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
Kezheng Xiong, Haoen Xiang, Qingshan Xu, Chenglu Wen, Siqi Shen, Jonathan Li, Cheng Wang