Modality Registration

Modality registration aims to align images or data from different sources (e.g., MRI, CT, LiDAR, ultrasound) to create a unified representation, facilitating integrated analysis and improved diagnostic or analytical capabilities. Current research emphasizes developing robust and efficient algorithms, often employing deep learning architectures like convolutional neural networks (CNNs) and incorporating techniques such as contrastive learning and probabilistic methods for improved accuracy and handling of complex deformations. These advancements are significantly impacting various fields, including autonomous driving, medical imaging (e.g., neurosurgery, bone disease analysis), and biomedical research, by enabling more precise and comprehensive analyses of multi-modal data.