# Multi-modal analysis of genetically-related subjects using SIFT descriptors in brain MRI

arXiv: https://arxiv.org/abs/1709.06151 · HTML: https://mlsanity.com/paper/1709.06151/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2017.

## Built on by (most cited first, 1 of 1)

- [Registering Image Volumes using 3D SIFT and Discrete SP-Symmetry](https://mlsanity.com/paper/2205.15456/) (2022)

## Abstract (arXiv)

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.