{"id":"https://openalex.org/W7161796641","doi":"https://doi.org/10.1109/isbi61048.2026.11515449","title":"Learning with Geometric Priors in U-Net Variants for Polyp Segmentation","display_name":"Learning with Geometric Priors in U-Net Variants for Polyp Segmentation","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7161796641","doi":"https://doi.org/10.1109/isbi61048.2026.11515449"},"language":null,"primary_location":{"id":"doi:10.1109/isbi61048.2026.11515449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi61048.2026.11515449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","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/A5048984855","display_name":"Fabian Vazquez","orcid":"https://orcid.org/0000-0002-1876-2092"},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fabian Vazquez","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123905946","display_name":"Jose A. Nu\u00f1ez","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jose A. Nu\u00f1ez","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077605534","display_name":"Diego Adame","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Diego Adame","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123977284","display_name":"Alissen Moreno","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alissen Moreno","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123932547","display_name":"Augustin Zhan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125989","display_name":"Sewickley Valley Hospital","ror":"https://ror.org/03c8ed890","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210125989"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Augustin Zhan","raw_affiliation_strings":["Sewickley Academy,Sewickley,PA,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sewickley Academy,Sewickley,PA,USA","institution_ids":["https://openalex.org/I4210125989"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135362518","display_name":"Huimin Li","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huimin Li","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124002519","display_name":"Jinghao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinghao Yang","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079922796","display_name":"Haoteng Tang","orcid":"https://orcid.org/0000-0003-0323-1755"},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haoteng Tang","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136512625","display_name":"Bin Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Fu","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136611149","display_name":"Pengfei Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I2802326326","display_name":"The University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12","country_code":"US","type":"education","lineage":["https://openalex.org/I2802326326"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pengfei Gu","raw_affiliation_strings":["The University of Texas Rio Grande Valley,Edinburg,TX,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas Rio Grande Valley,Edinburg,TX,USA","institution_ids":["https://openalex.org/I2802326326"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5048984855"],"corresponding_institution_ids":["https://openalex.org/I2802326326"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.9388437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.17180000245571136,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.17180000245571136,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.05860000103712082,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.03680000081658363,"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/prior-probability","display_name":"Prior probability","score":0.6371999979019165},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5605999827384949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5242999792098999},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4099999964237213},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.29840001463890076},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.29109999537467957}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6826000213623047},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6371999979019165},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5605999827384949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5465999841690063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5242999792098999},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4099999964237213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4016000032424927},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29840001463890076},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.29109999537467957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2906000018119812},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25029999017715454},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi61048.2026.11515449","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi61048.2026.11515449","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2352509956","display_name":null,"funder_award_id":"CCF2523787","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320314778","display_name":"University of Texas Rio Grande Valley","ror":"https://ror.org/02p5xjf12"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2008359794","https://openalex.org/W2021088830","https://openalex.org/W2285968993","https://openalex.org/W2560328367","https://openalex.org/W2939157633","https://openalex.org/W2997286550","https://openalex.org/W3092344722","https://openalex.org/W4214520160","https://openalex.org/W4289752563","https://openalex.org/W4327989205","https://openalex.org/W4401749956","https://openalex.org/W4402727359","https://openalex.org/W4402915538","https://openalex.org/W4407489980","https://openalex.org/W4410296772","https://openalex.org/W4412030481","https://openalex.org/W4413146238"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"and":[1,12,21,35,118,127,134,159],"robust":[2],"polyp":[3,66,87,148],"segmentation":[4,149],"is":[5,132],"essential":[6],"for":[7,13,65],"early":[8],"colorectal":[9],"cancer":[10],"detection":[11],"computer-aided":[14],"diagnosis.":[15],"While":[16],"convolutional":[17],"neural":[18],"network-,":[19],"Transformer-,":[20],"Mamba-based":[22],"U-Net":[23,141],"variants":[24],"have":[25],"achieved":[26],"strong":[27,156],"performance,":[28],"they":[29,112],"still":[30],"struggle":[31],"to":[32,82,90,102],"capture":[33],"geometric":[34,60,104],"structural":[36],"cues,":[37],"especially":[38],"in":[39],"low-contrast":[40],"or":[41],"cluttered":[42],"colonoscopy":[43],"scenes.":[44],"To":[45],"address":[46],"this":[47],"challenge,":[48],"we":[49,69],"propose":[50],"a":[51,78],"novel":[52],"Geometric":[53],"Prior-guided":[54],"Module":[55],"(GPM)":[56],"that":[57,122],"injects":[58],"explicit":[59],"priors":[61,105],"into":[62,106,139],"U-Net-based":[63],"architectures":[64],"segmentation.":[67],"Specifically,":[68],"fine-tune":[70],"the":[71,91,107,160],"Visual":[72],"Geometry":[73],"Grounded":[74],"Transformer":[75],"(VGGT)":[76],"on":[77,145],"simulated":[79],"ColonDepth":[80],"dataset":[81],"estimate":[83],"depth":[84,95,162],"maps":[85,96,163],"of":[86],"images":[88],"tailored":[89],"endoscopic":[92],"domain.":[93],"These":[94],"are":[97,113,164],"then":[98],"processed":[99],"by":[100],"GPM":[101,131],"encode":[103],"encoder's":[108],"feature":[109],"maps,":[110],"where":[111],"further":[114],"refined":[115],"using":[116],"spatial":[117,126],"channel":[119,129],"attention":[120],"mechanisms":[121],"emphasize":[123],"both":[124],"local":[125],"global":[128],"information.":[130],"plug-and-play":[133],"can":[135],"be":[136],"seamlessly":[137],"integrated":[138],"diverse":[140],"variants.":[142],"Extensive":[143],"experiments":[144],"five":[146],"public":[147],"datasets":[150],"demonstrate":[151],"consistent":[152],"gains":[153],"over":[154],"three":[155],"baselines.":[157],"Code":[158],"generated":[161],"available":[165],"at:":[166],"https://github.com/fvazqu/GPM-PolypSeg":[167]},"counts_by_year":[],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2026-05-21T00:00:00"}
