Multi-modal Analysis Of Genetically-related Subjects Using SIFT Descriptors In Brain MRI
Kuldeep Kumar, Laurent Chauvin, Mathew Toews, Olivier Colliot, Christian Desrosiers . Proc. Computational Diffusion MRI MICCAI Workshop Quebec City Canada September 2017 2017 – 0 citations
So far, fingerprinting studies have focused on identifying features from single-modality MRI data, which capture individual characteristics in terms of brain structure, function, or white matter microstructure. However, due to the lack of a framework for comparing across multiple modalities, studies based on multi-modal data remain elusive. This paper presents a multi-modal analysis of genetically-related subjects to compare and contrast the information provided by various MRI modalities. The proposed framework represents MRI scans as bags of SIFT features, and uses these features in a nearest-neighbor graph to measure subject similarity. Experiments using the T1/T2-weighted MRI and diffusion MRI data of 861 Human Connectome Project subjects demonstrate strong links between the proposed similarity measure and genetic proximity.