Multi Modal Image Registration

Multi-modal image registration aims to accurately align images from different imaging modalities (e.g., MRI, CT, ultrasound), a crucial preprocessing step for many medical applications. Current research emphasizes developing robust and efficient algorithms, often leveraging deep learning architectures like VoxelMorph and incorporating novel similarity measures such as modality-agnostic distances or mutual information neural estimation to overcome challenges posed by varying image intensities and structures. These advancements are improving the accuracy and speed of registration, leading to better image-guided therapies, more precise anatomical measurements, and enhanced diagnostic capabilities.