{"doi":"10.1002/hbm.70350","title":"Comprehensive Segmentation of Deep Grey Nuclei From Structural <scp>MRI</scp> Data","abstract":"ABSTRACT There is a lack of tools for comprehensive and complete segmentation of deep grey nuclei using a single software for reproducibility and repeatability. We present a fast, accurate, and robust method for segmentation of deep grey nuclei (thalamic nuclei, basal ganglia, amygdala, claustrum, and red nucleus) from structural T 1 MRI data at conventional field strengths. We leveraged the improved contrast of white‐matter‐nulled imaging by using the recently proposed Histogram‐based Polynomial Synthesis (HIPS) to synthesize white‐matter nulled images from standard T 1 and then use a multi‐atlas segmentation with joint label fusion to segment deep grey nuclei. The method worked robustly on all field strengths (1.5/3/7T) and Dice coefficients ≥ 0.7 were achieved for all structures compared against manual segmentation ground truth. In conclusion, this method facilitates careful investigation of deep grey nuclei by enabling the use of conventional T 1 data from large public databases, which has not been possible hitherto due to lack of robust reproducible segmentation tools.","journal":"Human Brain Mapping","year":2025,"id":539900,"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":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.892,"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":1427828,"name":"Giuseppina Cogliandro","orcid":null,"position":1,"is_corresponding":false},{"id":445989,"name":"Thomas Hicks","orcid":"0000-0002-5349-2454","position":2,"is_corresponding":false},{"id":1343360,"name":"Dianne Patterson","orcid":"0000-0001-7518-3110","position":3,"is_corresponding":false},{"id":275769,"name":"Behroze Vachha","orcid":"0000-0001-7462-1422","position":4,"is_corresponding":false},{"id":1385193,"name":"Asma Hader","orcid":null,"position":5,"is_corresponding":false},{"id":583396,"name":"Mohammed Salman Shazeeb","orcid":"0000-0002-3175-8098","position":6,"is_corresponding":false},{"id":458402,"name":"Alberto Cacciola","orcid":"0000-0001-9412-4116","position":7,"is_corresponding":false},{"id":381495,"name":"Manojkumar Saranathan","orcid":"0000-0001-9020-9948","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T02:52:34.520788Z","pmid":"40985796","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":[]}