{"id":"https://openalex.org/W7126087495","doi":"https://doi.org/10.1109/bibm66473.2025.11356980","title":"ArbitraryFlow: Towards One Step Generative Biomedical Image Segmentation","display_name":"ArbitraryFlow: Towards One Step Generative Biomedical Image Segmentation","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126087495","doi":"https://doi.org/10.1109/bibm66473.2025.11356980"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092864630","display_name":"Pengju Lyu","orcid":"https://orcid.org/0009-0004-0863-8110"},"institutions":[{"id":"https://openalex.org/I4210091706","display_name":"Henan Academy of Sciences","ror":"https://ror.org/00hy87220","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091706"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengju Lyu","raw_affiliation_strings":["Henan Academy of Sciences,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Academy of Sciences,Zhengzhou,China","institution_ids":["https://openalex.org/I4210091706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115860825","display_name":"Haopeng Jing","orcid":null},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haopeng Jing","raw_affiliation_strings":["North China University of Water Resources and Electric Power,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North China University of Water Resources and Electric Power,Zhengzhou,China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122859318","display_name":"Chenglin Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091706","display_name":"Henan Academy of Sciences","ror":"https://ror.org/00hy87220","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091706"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglin Liu","raw_affiliation_strings":["Henan Academy of Sciences,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Academy of Sciences,Zhengzhou,China","institution_ids":["https://openalex.org/I4210091706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036426775","display_name":"Yuanbo He","orcid":"https://orcid.org/0000-0001-8656-4496"},"institutions":[{"id":"https://openalex.org/I4210091706","display_name":"Henan Academy of Sciences","ror":"https://ror.org/00hy87220","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091706"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanbo He","raw_affiliation_strings":["Henan Academy of Innovations in Medical Science,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan Academy of Innovations in Medical Science,Zhengzhou,China","institution_ids":["https://openalex.org/I4210091706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124218309","display_name":"Yuxin Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Xie","raw_affiliation_strings":["North China University of Water Resources and Electric Power,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North China University of Water Resources and Electric Power,Zhengzhou,China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wenjian Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Wenjian Liu","raw_affiliation_strings":["City University of Macau,Macau,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Macau,Macau,China","institution_ids":["https://openalex.org/I6469544"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"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":"1119","last_page":"1126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8876000046730042,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.8876000046730042,"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"}},{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.010999999940395355,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.008899999782443047,"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/segmentation","display_name":"Segmentation","score":0.6202999949455261},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5228000283241272},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5182999968528748},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4275999963283539},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.412200003862381},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4032999873161316},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.38179999589920044},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.37720000743865967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208999752998352},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6202999949455261},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5228000283241272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228000283241272},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5182999968528748},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4275999963283539},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4032999873161316},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.38179999589920044},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34540000557899475},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.3386000096797943},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33090001344680786},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.3093000054359436},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30309998989105225},{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2851000130176544},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25679999589920044},{"id":"https://openalex.org/C91188154","wikidata":"https://www.wikidata.org/wiki/Q186247","display_name":"Vector field","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356980","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6291492581367493}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2288892845","https://openalex.org/W2991372685","https://openalex.org/W3172681723","https://openalex.org/W4221163766","https://openalex.org/W4377695098","https://openalex.org/W4384925777","https://openalex.org/W4386047807","https://openalex.org/W4386352882","https://openalex.org/W4390805643","https://openalex.org/W4390872297","https://openalex.org/W4391109864","https://openalex.org/W4393154023","https://openalex.org/W4403066927","https://openalex.org/W4403152107","https://openalex.org/W4408744579","https://openalex.org/W4409367393"],"related_works":[],"abstract_inverted_index":{"Biomedical":[0],"image":[1,254],"segmentation":[2,25,83,178],"has":[3],"witnessed":[4],"significant":[5],"advancements":[6],"through":[7,26,90],"deep":[8],"learning,":[9],"wherein":[10],"diffusionbased":[11],"generative":[12,237],"models":[13],"have":[14],"emerged":[15],"as":[16,84],"compelling":[17],"alternatives":[18],"to":[19,45,133,181,209],"traditional":[20],"discriminative":[21],"methodologies":[22],"by":[23,38,52],"reconceptualizing":[24],"an":[27,91,118],"image-guided":[28],"noise-to-mask":[29],"generation":[30],"paradigm.":[31],"Yet,":[32],"their":[33],"clinical":[34,67,241],"deployment":[35],"remains":[36],"constrained":[37],"intensive":[39],"iterative":[40],"denoising":[41],"procedures":[42],"necessitating":[43],"hundreds":[44],"thousands":[46],"of":[47,66,203,228],"model":[48],"function":[49],"evaluations,":[50],"compounded":[51],"inherent":[53],"stochastic":[54],"sampling":[55,189],"mechanisms":[56],"that":[57,81,101,116],"invariably":[58],"produce":[59],"non-deterministic":[60],"outputs":[61],"violating":[62],"the":[63,103,232],"consistency":[64],"imperatives":[65],"decision-making":[68],"requirements.":[69],"To":[70],"overcome":[71],"these":[72],"limitations,":[73],"we":[74],"propose":[75],"ArbitraryFlow,":[76],"a":[77,85,97,111,143,200],"deterministic":[78],"flowmatching":[79],"framework":[80,109],"reformulates":[82],"direct":[86],"image-to-mask":[87],"transport":[88,105],"problem":[89],"ordinary":[92],"differential":[93],"equation":[94],"(ODE)":[95],"modeling":[96],"continuous-time":[98],"velocity":[99,120,138],"field":[100,121,139],"governs":[102],"distribution":[104],"dynamics.":[106],"Crucially,":[107],"our":[108],"incorporates":[110],"two-time":[112],"flow":[113],"map":[114],"mechanism":[115],"learns":[117],"average":[119],"between":[122],"arbitrary":[123],"temporal":[124],"endpoints,":[125],"consequently":[126],"enabling":[127,239],"few(one)-step":[128],"mask":[129],"synthesis":[130],"without":[131],"recourse":[132],"ODE":[134],"integration":[135],"procedures.":[136],"The":[137],"is":[140,258],"instantiated":[141],"via":[142],"Diffusion":[144],"Transformer":[145],"(DiT)":[146],"backbone":[147],"equipped":[148],"with":[149,217,245],"adaptive":[150],"layer":[151],"normalization":[152],"for":[153,251],"effective":[154],"dual":[155],"time-conditioned":[156],"feature":[157],"modulation":[158],"while":[159,221],"preserving":[160,215],"parametric":[161],"and":[162,185],"computational":[163,223],"efficiency.":[164],"Comprehensive":[165],"experiments":[166],"across":[167],"three":[168],"multimodal":[169],"datasets":[170],"(MSD-BraTS,":[171],"GlaS,":[172],"BUSI)":[173],"demonstrate":[174],"ArbitraryFlow":[175,230],"achieves":[176],"superior":[177],"performance":[179],"relative":[180],"established":[182],"prior":[183],"arts":[184],"consistently":[186],"outperforms":[187],"alternative":[188],"acceleration":[190,224],"techniques":[191],"under":[192],"various":[193],"inference":[194],"budgets.":[195],"Its":[196],"single-step":[197],"instantiation":[198],"manifests":[199],"Dice":[201],"decline":[202],"less":[204],"than":[205],"1.5":[206],"%":[207],"compared":[208],"its":[210],"optimal":[211],"1000":[212],"step":[213],"configuration,":[214],"parity":[216],"exhaustive":[218],"diffusion":[219,246],"baselines":[220],"delivering":[222],"exceeding":[225],"two":[226],"orders":[227],"magnitude.":[229],"redefines":[231],"efficiency-":[233],"accuracy":[234],"trade-off":[235],"in":[236],"segmentation,":[238],"realtime":[240],"applications":[242],"previously":[243],"unattainable":[244],"paradigms,":[247],"opening":[248],"new":[249],"possibilities":[250],"real-time":[252],"biomedical":[253],"analysis.":[255],"Our":[256],"code":[257],"available":[259],"at":[260],"https://github.com/lyupengju/shortcut_flows.":[261]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}