{"id":"https://openalex.org/W7167693873","doi":"https://doi.org/10.1109/tip.2026.3707793","title":"LSR-Diff: A Diffusion Model Synthesizing Level Set Representations for Reliable Segmentation of Medical Images With Ambiguous Edges","display_name":"LSR-Diff: A Diffusion Model Synthesizing Level Set Representations for Reliable Segmentation of Medical Images With Ambiguous Edges","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7167693873","doi":"https://doi.org/10.1109/tip.2026.3707793","pmid":"https://pubmed.ncbi.nlm.nih.gov/42418383"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3707793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3707793","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5017828790","display_name":"Wenbo Gao","orcid":"https://orcid.org/0000-0002-4471-1870"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Gao","raw_affiliation_strings":["Harbin Institute of Technology, School of Science, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0005-3481-9908","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, School of Science, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114888743","display_name":"Haoyu Cao","orcid":"https://orcid.org/0009-0003-5311-4546"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Cao","raw_affiliation_strings":["Harbin Institute of Technology, School of Science, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-5311-4546","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, School of Science, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047913546","display_name":"James Chung\u2010Wai Cheung","orcid":"https://orcid.org/0000-0001-7446-0569"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"James Chung-Wai Cheung","raw_affiliation_strings":["Research Institute of Smart Ageing and the Research Institute for Sports Science and Technology, The Hong Kong Polytechnic University, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7446-0569","affiliations":[{"raw_affiliation_string":"Research Institute of Smart Ageing and the Research Institute for Sports Science and Technology, The Hong Kong Polytechnic University, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090906323","display_name":"Yunyun Yang","orcid":"https://orcid.org/0000-0002-0488-7652"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyun Yang","raw_affiliation_strings":["Harbin Institute of Technology, School of Science, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-0488-7652","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, School of Science, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87414181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"7277","last_page":"7292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.6764000058174133,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.6764000058174133,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.1437000036239624,"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/T11019","display_name":"Image Enhancement Techniques","score":0.017400000244379044,"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/image-segmentation","display_name":"Image segmentation","score":0.6148999929428101},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5523999929428101},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5436000227928162},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.5408999919891357},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4553999900817871},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4404999911785126},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4092000126838684},{"id":"https://openalex.org/keywords/level-set-method","display_name":"Level set method","score":0.3537999987602234}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6859999895095825},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6148999929428101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6050000190734863},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5565999746322632},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5523999929428101},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5436000227928162},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.5408999919891357},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4404999911785126},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4092000126838684},{"id":"https://openalex.org/C125269122","wikidata":"https://www.wikidata.org/wiki/Q1751397","display_name":"Level set method","level":4,"score":0.3537999987602234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3215999901294708},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.3124000132083893},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30820000171661377},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C2994222927","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grey level","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C185568154","wikidata":"https://www.wikidata.org/wiki/Q530242","display_name":"Mathematical morphology","level":4,"score":0.25929999351501465},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.2581999897956848},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.25609999895095825}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3707793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3707793","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:42418383","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42418383","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,"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":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1054334880","display_name":null,"funder_award_id":"JCYJ20240813105132043","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6969874819","display_name":null,"funder_award_id":"62371156","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"boundary":[1,19,35,121,181],"segmentation":[2,46],"is":[3],"critical":[4],"for":[5],"high-stakes":[6],"applications":[7,200],"such":[8],"as":[9],"disease":[10],"diagnosis,":[11],"yet":[12],"remains":[13],"challenging":[14],"due":[15],"to":[16,38,60,84,118,138,164],"complex":[17],"topology,":[18,182],"ambiguity,":[20],"and":[21,58,74,89,123,156,176,204,213,217],"annotation":[22],"uncertainty.":[23],"Diffusion":[24],"Probabilistic":[25],"Models":[26],"(DPMs)":[27],"generate":[28],"multiple":[29,202],"masks":[30,155],"with":[31,53,113,160],"inherent":[32],"uncertainty,":[33],"enhancing":[34],"delineation":[36],"compared":[37],"deterministic":[39],"models.":[40],"However,":[41],"most":[42],"existing":[43],"DPM":[44],"based":[45],"approaches":[47],"learn":[48],"discrete":[49,153],"binary":[50,154],"masks,":[51,159],"conflicting":[52],"the":[54,67,97,188,221],"continuous":[55,157],"diffusion":[56,111],"process":[57],"leading":[59,83],"hard-to-learn":[61],"degradation":[62],"during":[63,187],"noise":[64],"addition.":[65],"Moreover,":[66],"prevailing":[68],"approach":[69],"of":[70,151,190],"averaging":[71],"stochastic":[72,191],"predictions":[73],"applying":[75],"a":[76,110,114,124,166],"fixed":[77],"threshold":[78],"disregards":[79],"structural":[80,144],"consistency,":[81],"often":[82],"imprecise":[85],"boundaries,":[86],"isolated":[87],"artifacts,":[88],"holes.":[90],"To":[91],"address":[92],"these":[93],"challenges,":[94],"we":[95],"propose":[96],"$L$":[98],"evel":[99],"$S$":[100,133],"et":[101,134],"$R$":[102],"epresentation":[103],"$D$":[104],"iffusion":[105],"model":[106,112],"(LSR-Diff),":[107],"which":[108],"incorporates":[109],"hybrid":[115,147],"mask":[116,185],"representation":[117,148,163],"better":[119],"capture":[120],"information,":[122],"novel":[125],"strategy":[126],"$E$":[127,135],"nsemble":[128],"$A$":[129],"ggregation":[130],"via":[131],"Level":[132],"volution":[136],"(EASE)":[137],"merge":[139],"prediction":[140],"candidates":[141],"while":[142],"respecting":[143],"information.":[145],"The":[146,169],"takes":[149],"advantage":[150],"both":[152],"implicit":[158],"an":[161],"intermediate":[162],"ensure":[165],"smooth":[167],"transition.":[168],"EASE":[170],"module":[171],"guided":[172],"by":[173],"ambiguity":[174],"estimation":[175],"anatomical":[177],"structure":[178],"then":[179],"refines":[180],"preventing":[183],"arbitrary":[184],"assembly":[186],"aggregation":[189],"predictions.":[192],"We":[193],"conduct":[194],"extensive":[195],"experiments":[196],"across":[197],"various":[198],"clinical":[199],"including":[201],"modalities":[203],"tissues,":[205],"showing":[206],"that":[207],"LSR-Diff":[208],"achieves":[209],"competitive":[210],"overall":[211],"performance":[212],"improved":[214],"edge":[215],"quality":[216],"topology":[218],"accuracy":[219],"on":[220],"tested":[222],"tasks.":[223]},"counts_by_year":[],"updated_date":"2026-07-18T07:39:51.176621","created_date":"2026-07-09T00:00:00"}
