{"id":"https://openalex.org/W4417422338","doi":"https://doi.org/10.54097/wjyjqk67","title":"A Comparative Review of U-Net-Based Enhanced Polyp Segmentation Models: From Architectural Evolution to Multimodal Fusion","display_name":"A Comparative Review of U-Net-Based Enhanced Polyp Segmentation Models: From Architectural Evolution to Multimodal Fusion","publication_year":2025,"publication_date":"2025-12-17","ids":{"openalex":"https://openalex.org/W4417422338","doi":"https://doi.org/10.54097/wjyjqk67"},"language":"en","primary_location":{"id":"doi:10.54097/wjyjqk67","doi":"https://doi.org/10.54097/wjyjqk67","is_oa":true,"landing_page_url":"https://doi.org/10.54097/wjyjqk67","pdf_url":"https://jocsai.com/index.php/jcsai/article/download/126/125","source":{"id":"https://openalex.org/S5407049135","display_name":"Journal of Computer Science and Artificial Intelligence","issn_l":"3078-2309","issn":["3078-2309","3078-8242"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://jocsai.com/index.php/jcsai/article/download/126/125","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rihan Cai","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rihan Cai","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108843492","display_name":"Yingxin Wei","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingxin Wei","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rongyao Du","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongyao Du","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ji Peng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Peng","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wang Lu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Lu","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089973106","display_name":"Lixia He","orcid":"https://orcid.org/0000-0002-7729-0777","observed_orcids":["https://orcid.org/0000-0002-7729-0777"]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixia He","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103071679","display_name":"Botao Liu","orcid":"https://orcid.org/0009-0006-6656-0221","observed_orcids":["https://orcid.org/0009-0006-6656-0221","https://orcid.org/0000-0002-6963-957X"]},"institutions":[{"id":"https://openalex.org/I177739611","display_name":"Yangtze University","ror":"https://ror.org/05bhmhz54","country_code":"CN","type":"education","lineage":["https://openalex.org/I177739611"]},{"id":"https://openalex.org/I4387154485","display_name":"Key Laboratory of Drilling and Production Engineering for Oil and Gas, Hubei Province","ror":"https://ror.org/050t2pq94","country_code":"CN","type":"facility","lineage":["https://openalex.org/I177739611","https://openalex.org/I4387154485"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Botao Liu","raw_affiliation_strings":["College of Computer Science , Yangtze University , Jingzhou 434023 , China","Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering , Yangtze University , Jingzhou 434023 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611"]},{"raw_affiliation_string":"Hubei Key Laboratory of Oil and Gas Drilling and Production Engineering , Yangtze University , Jingzhou 434023 , China","institution_ids":["https://openalex.org/I177739611","https://openalex.org/I4387154485"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39566478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"2","first_page":"42","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9545999765396118,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9545999765396118,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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":0.021900000050663948,"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/T10862","display_name":"AI in cancer detection","score":0.016499999910593033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/polyp-segmentation","display_name":"polyp segmentation","score":0.871999979019165},{"id":"https://openalex.org/keywords/colorectal-polyps","display_name":"colorectal polyps","score":0.8349999785423279},{"id":"https://openalex.org/keywords/u-net-variants","display_name":"U-Net variants","score":0.8759999871253967},{"id":"https://openalex.org/keywords/endoscopic-image-segmentation","display_name":"endoscopic image segmentation","score":0.7490000128746033},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.6549999713897705},{"id":"https://openalex.org/keywords/cross-modal-fusion","display_name":"cross-modal fusion","score":0.6269999742507935},{"id":"https://openalex.org/keywords/vision-language-pre-training","display_name":"vision-language pre-training","score":0.875},{"id":"https://openalex.org/keywords/edge-aware-segmentation","display_name":"edge-aware segmentation","score":0.5569999814033508},{"id":"https://openalex.org/keywords/multiscale-feature-fusion","display_name":"multi-scale feature fusion","score":0.8199999928474426},{"id":"https://openalex.org/keywords/boundary-precision","display_name":"boundary precision","score":0.46000000834465027},{"id":"https://openalex.org/keywords/resunet","display_name":"ResUNet","score":0.6589999794960022},{"id":"https://openalex.org/keywords/colorectal-cancer-diagnosis","display_name":"colorectal cancer diagnosis","score":0.7630000114440918}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7803000211715698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7526000142097473},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7491999864578247},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6008999943733215},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4918000102043152},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.48240000009536743},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47909998893737793},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4535999894142151},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45089998841285706},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44200000166893005},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4262000024318695},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32760000228881836},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.3264999985694885},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.30970001220703125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3093000054359436},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.29789999127388},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.2937999963760376},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.54097/wjyjqk67","doi":"https://doi.org/10.54097/wjyjqk67","is_oa":true,"landing_page_url":"https://doi.org/10.54097/wjyjqk67","pdf_url":"https://jocsai.com/index.php/jcsai/article/download/126/125","source":{"id":"https://openalex.org/S5407049135","display_name":"Journal of Computer Science and Artificial Intelligence","issn_l":"3078-2309","issn":["3078-2309","3078-8242"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.54097/wjyjqk67","doi":"https://doi.org/10.54097/wjyjqk67","is_oa":true,"landing_page_url":"https://doi.org/10.54097/wjyjqk67","pdf_url":"https://jocsai.com/index.php/jcsai/article/download/126/125","source":{"id":"https://openalex.org/S5407049135","display_name":"Journal of Computer Science and Artificial Intelligence","issn_l":"3078-2309","issn":["3078-2309","3078-8242"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computer Science and Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5683000087738037}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417422338.pdf","grobid_xml":"https://content.openalex.org/works/W4417422338.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2592929672","https://openalex.org/W2928133111","https://openalex.org/W2996290406","https://openalex.org/W3092344722","https://openalex.org/W4390874575"],"related_works":["https://openalex.org/W4391184121","https://openalex.org/W7162703904","https://openalex.org/W4392190893","https://openalex.org/W7108465599","https://openalex.org/W7136676960","https://openalex.org/W7208748746","https://openalex.org/W4407901403","https://openalex.org/W7125792418","https://openalex.org/W7117669466","https://openalex.org/W7165404016"],"abstract_inverted_index":{"Colorectal":[0],"cancer":[1,15],"has":[2,44,279],"been":[3,65,280],"recognized":[4],"as":[5,67,161,245],"the":[6,11,24,33,47,57,74,102,113,131,190,225,256,272,276,307],"third":[7,12],"most":[8,13],"prevalent":[9],"and":[10,19,53,60,101,143,174,185,196,201,208,234,243,300],"lethal":[14],"worldwide.":[16],"Accurate":[17],"detection":[18,52,191],"segmentation":[20,54,119,218,312],"of":[21,36,41,49,104,117,193,250,258,275,310],"polyps":[22],"in":[23,31,70,260],"colorectal":[25],"region":[26],"play":[27],"a":[28,241,246],"crucial":[29],"role":[30],"facilitating":[32],"early":[34],"diagnosis":[35],"cancer.":[37],"The":[38],"rapid":[39],"advancement":[40],"deep":[42,311],"learning":[43],"greatly":[45],"accelerated":[46],"development":[48],"automated":[50],"polyp":[51,118,266],"techniques.":[55],"Although":[56],"well-established":[58],"U-Net":[59,76,122,277],"its":[61],"variants":[62],"have":[63],"long":[64],"regarded":[66],"classical":[68],"architectures":[69],"medical":[71],"image":[72],"segmentation,":[73],"basic":[75],"model":[77],"still":[78],"exhibits":[79],"several":[80],"limitations":[81],"when":[82],"applied":[83],"to":[84,126,168,215,292,304],"complex":[85],"endoscopic":[86],"scenarios.":[87],"These":[88],"include":[89],"noise":[90],"introduced":[91],"by":[92,179,205],"skip":[93],"connections,":[94],"restricted":[95],"receptive":[96],"fields":[97],"for":[98,147,265],"contextual":[99],"information,":[100],"absence":[103],"effective":[105],"edge-awareness":[106],"mechanisms.":[107],"This":[108,268],"review":[109,269],"systematically":[110],"elaborates":[111],"on":[112,121,170,294],"recent":[114,180,247],"research":[115,273,289],"progress":[116],"based":[120],"optimization":[123,284],"models.":[124,313],"According":[125],"different":[127],"structural":[128],"enhancement":[129],"strategies,":[130],"existing":[132],"methods":[133],"can":[134],"be":[135],"broadly":[136],"categorized":[137],"into":[138,240],"four":[139],"major":[140],"types:":[141],"Depth":[142],"residual":[144,155],"error":[145],"optimization.":[146,252],"example,":[148],"ResUNet++":[149],"[1]":[150],"enhances":[151],"gradient":[152],"propagation":[153],"through":[154],"connections.":[156],"Attention":[157,237],"mechanism":[158],"integration.":[159],"such":[160],"PraNet":[162],"[2],":[163],"which":[164,188,211],"employs":[165],"reverse":[166],"attention":[167],"focus":[169,293],"salient":[171],"regions.":[172],"Boundary":[173],"multi-scale":[175],"feature":[176],"fusion.":[177,287],"exemplified":[178],"models":[181],"like":[182],"CaraNet":[183],"[3]":[184],"BUNet":[186],"[4],":[187],"improve":[189,306],"accuracy":[192],"small":[194],"objects":[195],"enhance":[197],"boundary":[198],"precision.":[199],"Semantic":[200],"cross-modal":[202],"enhancement.":[203],"represented":[204],"TGA-Net":[206],"[5]":[207],"CLIP-Polyp":[209],"[6],":[210],"leverage":[212],"vision-language":[213],"pretraining":[214],"achieve":[216],"improved":[217],"performance.":[219],"Our":[220],"proposed":[221],"network,":[222],"MSEANet,":[223],"integrates":[224],"Edge":[226,236],"Feature":[227],"Extraction":[228],"(EFE),":[229],"Cross-layer":[230],"Context":[231],"Fusion":[232],"(CCF),":[233],"Selective":[235],"(SEA)":[238],"modules":[239],"framework":[242],"serves":[244],"work":[248],"representative":[249],"collaborative":[251],"Experimental":[253],"results":[254],"indicate":[255],"effectiveness":[257],"MSEANet":[259],"achieving":[261],"synergic":[262],"multi-module":[263],"fusion":[264],"segmentation.":[267],"finds":[270],"that":[271],"trajectory":[274],"family":[278],"developed":[281],"from":[282],"single-module":[283],"towards":[285],"multidimensional":[286],"Future":[288],"will":[290],"tend":[291],"light-weight":[295],"framework,":[296],"multimodal":[297],"semantic":[298],"guidance,":[299],"enhanced":[301],"interpretability,":[302],"designing":[303],"further":[305],"clinical":[308],"applicability":[309]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2025-12-17T00:00:00"}
