{"id":"https://openalex.org/W7214999848","doi":"https://doi.org/10.48550/arxiv.2609.36339","title":"Bridging cone-beam CT and MRI to stopping power ratio maps: a modality-agnostic Brownian bridge approach to support robust adaptive proton therapy","display_name":"Bridging cone-beam CT and MRI to stopping power ratio maps: a modality-agnostic Brownian bridge approach to support robust adaptive proton therapy","publication_year":2026,"publication_date":"2026-09-28","ids":{"openalex":"https://openalex.org/W7214999848","doi":"https://doi.org/10.48550/arxiv.2609.36339","pmid":"https://pubmed.ncbi.nlm.nih.gov/42856436","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13648775"},"language":"en","primary_location":{"id":"pmid:42856436","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42856436","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ArXiv","raw_type":"Journal Article"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13648775/","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101053553","display_name":"Yuhao Yan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan, Yuhao","raw_affiliation_strings":["Department of Medical Physics , University of Wisconsin-Madison , Madison , WI , USA","Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medical Physics , University of Wisconsin-Madison , Madison , WI , USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153661932","display_name":"Qisheng He","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154057602","display_name":"Henry Ford Health","ror":"https://ror.org/02kwnkm68","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I154057602"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"He, Qisheng","raw_affiliation_strings":["Henry Ford Health , Detroit , MI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henry Ford Health , Detroit , MI , USA","institution_ids":["https://openalex.org/I154057602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153593899","display_name":"Minglei Kang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kang, Minglei","raw_affiliation_strings":["Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090725409","display_name":"Behzad Hejrati","orcid":"https://orcid.org/0000-0002-6190-915X","observed_orcids":["https://orcid.org/0000-0002-6190-915X"]},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hejrati, Behzad","raw_affiliation_strings":["Department of Computer Science , Wayne State University , Detroit , MI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Wayne State University , Detroit , MI , USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153585073","display_name":"Christian Hyde","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyde, Christian","raw_affiliation_strings":["Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Medicine , University of Wisconsin-Madison , Madison , WI , USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5153637466","display_name":"Ming Dong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong, Ming","raw_affiliation_strings":["Department of Computer Science , Wayne State University , Detroit , MI , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Wayne State University , Detroit , MI , USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140982555","display_name":"Carri Glide\u2010Hurst","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Glide-Hurst, Carri","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11176","display_name":"Radiation Therapy and Dosimetry","score":0.7461000084877014,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11176","display_name":"Radiation Therapy and Dosimetry","score":0.7461000084877014,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.24060000479221344,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptive-proton-therapy","display_name":"adaptive proton therapy","score":0.9129999876022339},{"id":"https://openalex.org/keywords/stopping-power-ratio","display_name":"stopping power ratio","score":0.7390000224113464},{"id":"https://openalex.org/keywords/cone-beam-computed-tomography","display_name":"cone-beam computed tomography","score":0.8299999833106995},{"id":"https://openalex.org/keywords/conditional-gan","display_name":"conditional generative adversarial networks","score":0.8679999709129333},{"id":"https://openalex.org/keywords/head-and-neck-cancer","display_name":"head and neck cancer","score":0.8330000042915344},{"id":"https://openalex.org/keywords/proton-dose-calculation","display_name":"proton dose calculation","score":0.5580000281333923},{"id":"https://openalex.org/keywords/ct-simulation","display_name":"CT simulation","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C21596040","wikidata":"https://www.wikidata.org/wiki/Q2896771","display_name":"Unimodality","level":2,"score":0.5594000220298767},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5485000014305115},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.5418000221252441},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5055999755859375},{"id":"https://openalex.org/C78651780","wikidata":"https://www.wikidata.org/wiki/Q628309","display_name":"Brownian bridge","level":3,"score":0.427700012922287},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38190001249313354},{"id":"https://openalex.org/C187954543","wikidata":"https://www.wikidata.org/wiki/Q1501273","display_name":"Hounsfield scale","level":3,"score":0.3596999943256378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3562000095844269},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.337799996137619},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2962000072002411},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.26989999413490295},{"id":"https://openalex.org/C2779244869","wikidata":"https://www.wikidata.org/wiki/Q507667","display_name":"Proton therapy","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C2781204021","wikidata":"https://www.wikidata.org/wiki/Q6497091","display_name":"Lattice (music)","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C104409967","wikidata":"https://www.wikidata.org/wiki/Q1054836","display_name":"Homoscedasticity","level":3,"score":0.259799987077713},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.25949999690055847},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C112401455","wikidata":"https://www.wikidata.org/wiki/Q178036","display_name":"Brownian motion","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":4,"locations":[{"id":"pmid:42856436","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42856436","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ArXiv","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13648775","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13648775/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ArXiv","raw_type":"Text"},{"id":"pmh:oai:arXiv.org:2609.36339","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.36339","pdf_url":"https://arxiv.org/pdf/2609.36339","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.36339","doi":"https://doi.org/10.48550/arxiv.2609.36339","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.36339","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:13648775","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13648775/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ArXiv","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.9391000270843506}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1660390707","display_name":"Reducing cardiac toxicity with deep learning and MRI-guided radiation therapy","funder_award_id":"R01HL153720","funder_id":"https://openalex.org/F4320337338","funder_display_name":"National Heart, Lung, and Blood Institute"}],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337338","display_name":"National Heart, Lung, and Blood Institute","ror":"https://ror.org/012pb6c26"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214999848.pdf","grobid_xml":"https://content.openalex.org/works/W7214999848.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W3122887982","https://openalex.org/W4406793953"],"related_works":["https://openalex.org/W7207162183","https://openalex.org/W3011187476","https://openalex.org/W3037123803","https://openalex.org/W4402945486","https://openalex.org/W4417274856","https://openalex.org/W6927091532","https://openalex.org/W6996222355","https://openalex.org/W7172480587","https://openalex.org/W6927390848","https://openalex.org/W4411986757"],"abstract_inverted_index":{"Objective:":[0],"Adaptive":[1],"proton":[2],"therapy":[3],"(APT)":[4],"relies":[5],"on":[6],"routine":[7],"offline":[8],"CT":[9],"simulations":[10],"for":[11,77,96,130],"updated":[12],"anatomy.":[13],"To":[14],"facilitate":[15],"APT,":[16],"we":[17],"present":[18],"a":[19,49,63],"high\u2011fidelity,":[20],"modality-agnostic":[21,174,193],"regularized":[22],"Brownian":[23,50],"bridge":[24,51],"(rBBrg)":[25],"framework":[26],"to":[27,118,125,178,198,207],"deterministically":[28],"predict":[29],"stopping":[30],"power":[31],"ratio":[32,145],"(SPR)":[33],"maps":[34,136],"from":[35,56,70,106,203],"cone-beam":[36],"CTs":[37],"(CBCTs)":[38],"or":[39,205],"MRIs.":[40],"Approach:":[41],"rBBrg":[42,89,175,194],"consisted":[43],"of":[44,157],"(1)":[45],"generation":[46],"mapping":[47,61],"where":[48,62],"diffusion":[52],"model":[53,195],"predicted":[54,71],"SPR":[55,135,170,202],"input":[57,69],"and":[58,90,102,113,146,152,168,210],"(2)":[59],"reconstruction":[60],"conditional":[64],"generative":[65],"adversarial":[66],"network":[67,92],"reconstructed":[68],"SPR.":[72,133],"Class":[73],"embedding":[74],"was":[75,83,123,196],"adopted":[76],"modality":[78],"conditioning.":[79],"Efficient,":[80],"deterministic":[81,201],"prediction":[82],"achieved":[84],"via":[85,139],"one-step":[86],"sampling.":[87],"Unimodality":[88],"residual":[91],"(ResNet)":[93],"were":[94,110,115,137,171],"implemented":[95],"comparison.":[97],"Matched-pair":[98],"planning":[99,103],"CT-CBCT":[100],"(n=37)":[101],"CT-MRI":[104],"(n=21)":[105],"head-and-neck":[107],"cancer":[108],"patients":[109],"evaluated.":[111],"CBCTs":[112],"MRIs":[114],"deformably":[116],"registered":[117],"CTs.":[119],"A":[120,191],"calibration":[121],"phantom":[122],"scanned":[124],"establish":[126],"Hounsfield":[127],"look-up":[128],"table":[129],"ground":[131,150],"truth":[132,151],"Predicted":[134],"evaluated":[138],"mean":[140],"absolute":[141],"error":[142],"(MAE),":[143],"peak-signal-to-noise":[144],"structural":[147],"similarity":[148],"between":[149,166],"predictions":[153,176],"along":[154],"with":[155,180],"demonstration":[156],"dosimetric":[158],"performance.":[159],"Main":[160],"results:":[161],"=0.057\u00b10.005.":[162],"Dose":[163],"calculation":[164],"comparisons":[165],"real":[167],"CBCT-predicted":[169],"higher":[172],"in":[173],"compared":[177],"ResNet":[179],"gamma":[181],"pass":[182],"rate=98.8%/99.3%":[183],"vs":[184],"94.5%/96.9%":[185],"at":[186],"2":[187],"mm/2%,":[188],"respectively.":[189],"Significance:":[190],"novel":[192],"developed":[197],"generate":[199],"high-fidelity,":[200],"CBCT":[204],"MRI":[206],"support":[208],"efficient":[209],"flexible":[211],"APT":[212],"workflow.":[213],"Initial":[214],"feasibility":[215],"has":[216],"been":[217],"established.":[218]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-01T00:00:00"}