{"doi":"10.1109/tbme.2025.3614233","title":"Detecting Beta-Amyloid Plaque via Low Rank Based Orthogonal Projection and Spatial-Spectrum Detector Using High-Resolution Quantitative Susceptibility Mapping for Preclinical Studies","abstract":"Detecting beta-amyloid (A$\\beta$) plaques at different stages is crucial for accurate assessment and effective intervention in Alzheimer's disease (AD). In this study, we developed a novel method for reliably identifying A$\\beta$ plaques, characterized by sparse negative susceptibility values, in preclinical studies using high-resolution quantitative susceptibility mapping (QSM), named QSM-PLAQUE A$\\beta$ Detector. This approach decomposes a high-resolution QSM MRI image into three components: L (representing the background subspace), S (representing the signals subspace), and N (representing the noise). Subsequently, we established an orthogonal subspace based on L to eliminate the background from the sum of L and S. Finally, a plaque detection process was conducted, where A$\\beta$ plaques were identified based on the neighbor spectrum (NS) of a voxel being tested rather than just analyzing the voxel itself alone. Experiments demonstrated that the proposed method effectively detects A$\\beta$ plaques of varying shapes and intensities across the entire mouse brain. It shows robust performance across histology, high-resolution QSM MRI, and synthesized datasets, without requiring training samples. The QSM-PLAQUE A$\\beta$ Detector provides a practical framework for identifying and visualizing A$\\beta$ plaques in preclinical studies, offering a new strategy for quantitative assessment of A$\\beta$ plaques and may guide the development of advanced techniques for preclinical AD research.","journal":"IEEE Transactions on Biomedical Engineering","year":2025,"id":575715,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.961,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"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":970416,"name":"Xinyue Han","orcid":"0000-0002-8082-0863","position":1,"is_corresponding":false},{"id":1484313,"name":"Zhuoheng Liu","orcid":null,"position":2,"is_corresponding":false},{"id":73722,"name":"C. Zhou","orcid":"0000-0002-9034-4426","position":3,"is_corresponding":false},{"id":1483945,"name":"Rui Hu","orcid":"0000-0002-5860-9148","position":4,"is_corresponding":false},{"id":1484314,"name":"Saira Tabassam","orcid":null,"position":5,"is_corresponding":false},{"id":1067990,"name":"Season K. Wyatt‐Johnson","orcid":"0000-0001-8530-7885","position":6,"is_corresponding":false},{"id":285575,"name":"Adrian L. Oblak","orcid":"0000-0003-1210-8791","position":7,"is_corresponding":false},{"id":378955,"name":"Randy R. Brutkiewicz","orcid":"0000-0002-7396-480X","position":8,"is_corresponding":false},{"id":678125,"name":"Mingquan Lin","orcid":"0000-0003-0862-6588","position":9,"is_corresponding":false},{"id":928975,"name":"Nian Wang","orcid":"0000-0002-8303-0365","position":10,"is_corresponding":false},{"id":1483944,"name":"J. Chen","orcid":"0000-0002-4853-5341","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:57:52.712371Z","pmid":"40991598","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":[]}