The process of registration of medical images is one of the most fundamental in this field. It arises in various contexts, including when images from different individuals are mapped to a standardized coordinate system or atlas, thereby accounting for inter-individual anatomical variations, or when the scan of a patient is mapped to a later scan at a follow-up examination, in which anatomical change has likely occurred. Our group has a long-standing involvement in deformable registration methods[1-4], with particular emphasis on the use of rich imaging feature vectors as drivers of deformable registration, as well the use of the concept of mutual saliency as a means for weighting registration transformations according to regional confidence in the detected matches.
Current Projects:
- Deformable Registration via Attribute Matching and Mutual-Saliency Weighting — DRAMMS
- Pre-Operative and post-Recurrence brain Tumor Registration — PORTR
- Spatial Alignment of fMRI data — fMRI
Publications
- Davatzikos C: Spatial transformation and registration of brain images using elastically deformable models. Computer Vision and Image Understanding 1997, 66(2):207-222.
- Shen D, Davatzikos C: HAMMER: hierarchical attribute matching mechanism for elastic registration. IEEE transactions on medical imaging 2002, 21(11):1421-1439.
- Ou Y, Sotiras A, Paragios N, Davatzikos C: DRAMMS: Deformable registration via attribute matching and mutual-saliency weighting. Medical image analysis 2011, 15(4):622-639.
- Ou Y, Akbari H, Bilello M, Da X, Davatzikos C: Comparative Evaluation of Registration Algorithms in Different Brain Databases with Varying Difficulty: Results and Insights. IEEE transactions on medical imaging 2014.