{"doi":"10.1117/1.jmi.12.2.024006","title":"Multi-contrast computed tomography atlas of healthy pancreas with dense displacement sampling registration","abstract":"Purpose: Diverse population demographics can lead to substantial variation in the human anatomy. Therefore, standard anatomical atlases are needed for interpreting organ-specific analyses. Among abdominal organs, the pancreas exhibits notable variability in volumetric morphology, shape, and appearance, complicating the generalization of population-wide features. Understanding the common features of a healthy pancreas is crucial for identifying biomarkers and diagnosing pancreatic diseases. Approach: We propose a high-resolution CT atlas framework optimized for the healthy pancreas. We introduce a deep-learning-based preprocessing technique to extract abdominal ROIs and leverage a hierarchical registration pipeline to align pancreatic anatomy across populations. Briefly, DEEDS affine and non-rigid registration techniques are employed to transfer patient abdominal volumes to a fixed high-resolution atlas template. To generate and evaluate the pancreas atlas, multi-phase contrast CT scans of 443 subjects (aged 15 to 50 years, with no reported history of pancreatic disease) were processed. Results: The two-stage DEEDS affine and non-rigid registration outperforms other state-of-the-art tools, achieving the highest scores for pancreas label transfer across all phases (non-contrast: 0.497, arterial: 0.505, portal venous: 0.494, delayed: 0.497). External evaluation with 100 portal venous scans and 13 labeled abdominal organs shows a mean Dice score of 0.504. The low variance between the pancreases of registered subjects and the obtained pancreas atlas further illustrates the generalizability of the proposed method. Conclusion: We introduce a high-resolution pancreas atlas framework to generalize healthy biomarkers across populations with multi-contrast abdominal CT. The atlases and the associated pancreas organ labels are publicly available through the Human Biomolecular Atlas Program (HuBMAP).","journal":"Journal of Medical Imaging","year":2025,"id":543811,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":22.178386323199504,"corpus_rank":9377,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6765,"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":789857,"name":"Ho Hin Lee","orcid":"0000-0002-7378-2379","position":1,"is_corresponding":false},{"id":425889,"name":"Yucheng Tang","orcid":"0000-0002-6008-9700","position":2,"is_corresponding":false},{"id":379451,"name":"Xin Yu","orcid":"0000-0001-8996-0267","position":3,"is_corresponding":false},{"id":1020067,"name":"Qi Yang","orcid":"0000-0003-0530-0515","position":4,"is_corresponding":false},{"id":1167009,"name":"Michael E. Kim","orcid":"0009-0006-3562-2688","position":5,"is_corresponding":false},{"id":737882,"name":"Lucas W. Remedios","orcid":null,"position":6,"is_corresponding":false},{"id":425888,"name":"Shunxing Bao","orcid":"0000-0001-6376-4292","position":7,"is_corresponding":false},{"id":232770,"name":"Jeffrey M. Spraggins","orcid":"0000-0001-9198-5498","position":8,"is_corresponding":false},{"id":291228,"name":"Yuankai Huo","orcid":"0000-0002-2096-8065","position":9,"is_corresponding":false},{"id":104551,"name":"Bennett A. Landman","orcid":"0000-0001-5733-2127","position":10,"is_corresponding":false},{"id":1020624,"name":"Yinchi Zhou","orcid":null,"position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:53:08.338070Z","pmid":"40255249","pmcid":"PMC12005954","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":[]}