Multi-Modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification

Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye

Abstract: Schizophrenia (SZ) is a severe brain disorder marked by diverse cognitive impairments, abnormalities in brain structure, function, and genetic factors. Its complex symptoms and overlap with other psychiatric conditions complicate diagnosis, necessitating advanced systems. Existing research studies have mostly focused on imaging data, such as structural and functional MRI, for SZ diagnosis. There has been less focus on the integration of genomic features despite their potential in identifying heritable SZ traits. This study introduces a Multi-modal Imaging Genomics Transformer (MIGTrans) that integrates genomics with structural and functional imaging to identify SZ-related abnormalities. MIGTrans improved SZ classification accuracy to 86.05%, offering clear interpretations and identifying key genomic and brain morphological/connectivity patterns linked to SZ.

External IDs:dblp:conf/isbi/ShaikCCY25