{"id":"https://openalex.org/W7128790361","doi":"https://doi.org/10.48550/arxiv.2602.11703","title":"Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis","display_name":"Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis","publication_year":2026,"publication_date":"2026-02-12","ids":{"openalex":"https://openalex.org/W7128790361","doi":"https://doi.org/10.48550/arxiv.2602.11703"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.11703","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123340051","display_name":"Qiwen Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xu, Qiwen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123343321","display_name":"David R\u00fcgamer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R\u00fcgamer, David","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038151446","display_name":"Holger Wenz","orcid":"https://orcid.org/0000-0002-3463-5093"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenz, Holger","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108538756","display_name":"Johann Fontana","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fontana, Johann","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125983074","display_name":"Nora Meggyeshazi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meggyeshazi, Nora","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125970212","display_name":"Andreas Bender","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bender, Andreas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5008029296","display_name":"M\u00e1t\u00e9 E. Maros","orcid":"https://orcid.org/0000-0002-1589-8699"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maros, M\u00e1t\u00e9 E.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5123340051"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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/T10420","display_name":"Intracranial Aneurysms: Treatment and Complications","score":0.15569999814033508,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10420","display_name":"Intracranial Aneurysms: Treatment and Complications","score":0.15569999814033508,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.12870000302791595,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.08179999887943268,"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/similarity","display_name":"Similarity (geometry)","score":0.5921000242233276},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5400000214576721},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5047000050544739},{"id":"https://openalex.org/keywords/digital-subtraction-angiography","display_name":"Digital subtraction angiography","score":0.4853000044822693},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.47690001130104065},{"id":"https://openalex.org/keywords/likert-scale","display_name":"Likert scale","score":0.46549999713897705},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43540000915527344},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42329999804496765},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.39399999380111694}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323999762535095},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5921000242233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5608000159263611},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5400000214576721},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5047000050544739},{"id":"https://openalex.org/C2778286760","wikidata":"https://www.wikidata.org/wiki/Q1224954","display_name":"Digital subtraction angiography","level":3,"score":0.4853000044822693},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.47690001130104065},{"id":"https://openalex.org/C105776082","wikidata":"https://www.wikidata.org/wiki/Q617473","display_name":"Likert scale","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37940001487731934},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33640000224113464},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.31790000200271606},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.30379998683929443},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29829999804496765},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.11703","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.11703","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.11703","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2602.11703","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","score":0.49208059906959534,"display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Digital":[0],"subtraction":[1],"angiography":[2],"(DSA)":[3],"plays":[4],"a":[5,36,64,74,110,152],"central":[6],"role":[7],"in":[8],"the":[9],"diagnosis":[10],"and":[11,20,29,58,72,83,98,119,179],"treatment":[12],"of":[13,52,69,159],"cerebrovascular":[14],"disease,":[15],"yet":[16],"its":[17],"invasive":[18],"nature":[19],"high":[21,137],"acquisition":[22,84],"cost":[23],"severely":[24],"limit":[25],"large-scale":[26],"data":[27,31],"collection":[28],"public":[30],"sharing.":[32],"Therefore,":[33],"we":[34],"developed":[35],"semantically":[37,165],"conditioned":[38],"latent":[39],"diffusion":[40],"model":[41],"(LDM)":[42],"that":[43,80,164],"synthesizes":[44],"arterial-phase":[45],"cerebral":[46],"DSA":[47,67,107,147],"frames":[48,71,148],"under":[49],"explicit":[50],"control":[51],"anatomical":[53],"circulation":[54],"(anterior":[55],"vs.\\":[56],"posterior)":[57],"canonical":[59],"C-arm":[60],"positions.":[61],"We":[62],"curated":[63],"large":[65],"single-centre":[66],"dataset":[68],"99,349":[70],"trained":[73],"conditional":[75],"LDM":[76],"using":[77,109],"text":[78],"embeddings":[79],"encoded":[81],"anatomy":[82],"geometry.":[85],"To":[86],"assess":[87],"clinical":[88],"realism,":[89],"four":[90],"medical":[91],"experts,":[92],"including":[93],"two":[94],"neuroradiologists,":[95],"one":[96,99],"neurosurgeon,":[97],"internal":[100],"medicine":[101],"expert,":[102],"systematically":[103],"rated":[104],"400":[105],"synthetic":[106,171],"images":[108,125],"5-grade":[111],"Likert":[112,129],"scale":[113],"for":[114,174],"evaluating":[115],"proximal":[116],"large,":[117],"medium,":[118],"small":[120],"peripheral":[121],"vessels.":[122],"The":[123],"generated":[124],"achieved":[126],"image-wise":[127],"overall":[128],"scores":[130],"ranging":[131],"from":[132],"3.1":[133],"to":[134,145],"3.3,":[135],"with":[136],"inter-rater":[138],"reliability":[139],"(ICC(2,k)":[140],"=":[141],"0.80--0.87).":[142],"Distributional":[143],"similarity":[144],"real":[146],"was":[149],"supported":[150],"by":[151],"low":[153],"median":[154],"Fr\u00e9chet":[155],"inception":[156],"distance":[157],"(FID)":[158],"15.27.":[160],"Our":[161],"results":[162],"indicate":[163],"controlled":[166],"LDMs":[167],"can":[168],"produce":[169],"realistic":[170],"DSAs":[172],"suitable":[173],"downstream":[175],"algorithm":[176],"development,":[177],"research,":[178],"training.":[180]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2026-02-14T00:00:00"}
