HKMF: Hyperbolic Kernel-based Multimodal Fusion for HIV-Associated Neurocognitive Disorder Analysis

Motivation: HIV-associated neurocognitive disorder (HAND) has generally been studied through a single imaging modality like functional Magnetic Resonance Imaging (fMRI), which restricts understanding of its complex neuropathological causes. Goal(s): Our goal is to develop a multimodal approach that integrates fMRI and diffusion tensor imaging (DTI) for a more comprehensive HAND analysis. Approach: We introduce hyperbolic kernel-based multimodal fusion (HKMF), a new method for HAND analysis, combining fMRI and DTI data using hyperbolic geometry for more comprehensive insights. Results: Experimental results on 137 subjects show that our approach outperforms traditional methods in HAND diagnosis. Impact: HKMF utilizes hyperbolic geometry, which is well-suited for capturing complex hierarchies in neuroimaging applications. This approach not only enhances HAND analysis but also can be extended to other medical imaging applications involving multimodal datasets.