{"doi":"10.1109/bibe66822.2025.00042","title":"A Mixed Deep Neural Network for sMRI and fMR Features Fusion in AD Detection","abstract":"MRI(Magnetic Resonance Imaging), as a non-invasive imaging technology, provides rich information at both the structural and functional levels of brain, offering significant support for the screening of Alzheimer's disease (AD). However, due to the large heterogeneity in data format and spatial characteristics between sMRI and fMRI, achieving effective fusion of these two modalities remains a major challenge. To address this issue, we first designed a Transformer attention module incorporating 3D positional encoding to effectively encode 3D sMRI features. Next, we constructed a cascaded transformer module to address the feature encoding of fMRI and the multimodal feature fusion of MRI images from different spatial domains, thereby enhancing the feature representation of both modalities. Additionally, we adopted a multi-layer fused feature integration strategy to enhance the robustness of multimodal features. Visualization analysis is conducted to demonstrate the effectiveness of our method. And our method significantly outperforms single-modality methods using either sMRI or fMRI, exhibiting superior performance in the AD detection task.","journal":null,"year":2025,"id":559655,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.949,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1461481,"name":"Yuxiang Wei","orcid":"0000-0001-7408-6554","position":1,"is_corresponding":false},{"id":1461482,"name":"Yizhuo He","orcid":"0000-0001-7142-5338","position":2,"is_corresponding":false},{"id":227755,"name":"Anees Abrol","orcid":"0000-0001-9223-5314","position":3,"is_corresponding":false},{"id":227761,"name":"Vince D. Calhoun","orcid":"0000-0001-9058-0747","position":4,"is_corresponding":false},{"id":1064852,"name":"Yanteng Zhang","orcid":"0000-0003-4796-2904","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":null,"created_at":"2026-07-19T02:55:39.010633Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}