Multi-modal analysis of genetically-related subjects using SIFT descriptors in brain MRI
Abstract
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 microstruc-ture. 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.
Domains
Engineering Sciences [physics] Signal and Image processing Computer Science [cs] Computer Vision and Pattern Recognition [cs.CV] Computer Science [cs] Medical Imaging Computer Science [cs] Image Processing [eess.IV] Life Sciences [q-bio] Bioengineering Imaging Life Sciences [q-bio] Neurons and Cognition [q-bio.NC] Neurobiology
Origin : Files produced by the author(s)
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