{"id":"https://openalex.org/W4404740662","doi":"https://doi.org/10.1109/icbase63199.2024.10762635","title":"LRG-UNet:A Lightweight Randomized Grouped Feature Aggregation Enhanced UNet for Rectal Cancer Gland Segmentation","display_name":"LRG-UNet:A Lightweight Randomized Grouped Feature Aggregation Enhanced UNet for Rectal Cancer Gland Segmentation","publication_year":2024,"publication_date":"2024-09-20","ids":{"openalex":"https://openalex.org/W4404740662","doi":"https://doi.org/10.1109/icbase63199.2024.10762635"},"language":"en","primary_location":{"id":"doi:10.1109/icbase63199.2024.10762635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)","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/A5017810015","display_name":"Chuqi Chen","orcid":"https://orcid.org/0009-0009-9393-5238"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuqi Chen","raw_affiliation_strings":["Hebei University of Technology,College of Science,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology,College of Science,Tianjin,China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101715283","display_name":"Shengtao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengtao Zhang","raw_affiliation_strings":["Hebei University of Technology,College of Science,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology,College of Science,Tianjin,China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032423146","display_name":"Jia Zhao","orcid":"https://orcid.org/0000-0002-6917-4709"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Zhao","raw_affiliation_strings":["Hebei University of Technology,College of Science,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Technology,College of Science,Tianjin,China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17912761,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"915","last_page":"919"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9847000241279602,"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/T10862","display_name":"AI in cancer detection","score":0.9847000241279602,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9800999760627747,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/colorectal-cancer","display_name":"Colorectal cancer","score":0.5811173915863037},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5772438049316406},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5385488271713257},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5212655663490295},{"id":"https://openalex.org/keywords/randomized-controlled-trial","display_name":"Randomized controlled trial","score":0.41486990451812744},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.40531885623931885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2537063956260681},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1584259569644928},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15438568592071533}],"concepts":[{"id":"https://openalex.org/C526805850","wikidata":"https://www.wikidata.org/wiki/Q188874","display_name":"Colorectal cancer","level":3,"score":0.5811173915863037},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5772438049316406},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5385488271713257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5212655663490295},{"id":"https://openalex.org/C168563851","wikidata":"https://www.wikidata.org/wiki/Q1436668","display_name":"Randomized controlled trial","level":2,"score":0.41486990451812744},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.40531885623931885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2537063956260681},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1584259569644928},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15438568592071533},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icbase63199.2024.10762635","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icbase63199.2024.10762635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 5th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1950315773","https://openalex.org/W2288892845","https://openalex.org/W3015788359","https://openalex.org/W3016666924","https://openalex.org/W3120633509","https://openalex.org/W3127751679","https://openalex.org/W4321232185","https://openalex.org/W4387211614","https://openalex.org/W4390058606","https://openalex.org/W4390874124","https://openalex.org/W4392904379","https://openalex.org/W6739901393","https://openalex.org/W6798274885"],"related_works":["https://openalex.org/W2355769538","https://openalex.org/W2081816252","https://openalex.org/W2015216653","https://openalex.org/W2373885168","https://openalex.org/W2112436308","https://openalex.org/W2362391294","https://openalex.org/W3139914494","https://openalex.org/W2914553161","https://openalex.org/W1556819926","https://openalex.org/W3179965273"],"abstract_inverted_index":{"Colorectal":[0],"adenocarcinoma":[1,91,187],"is":[2,133,155,172],"a":[3,101,127],"common":[4],"malignancy":[5],"of":[6,16,20,45,69,81,204],"the":[7,42,64,73,77,124,147,162,175,181,191],"digestive":[8],"system,":[9],"posing":[10],"significant":[11],"threats":[12],"to":[13,135,146,226],"multiple":[14],"aspects":[15],"patients\u2019":[17],"health,":[18],"quality":[19],"life,":[21],"and":[22,25,38,55,67,79,109,202,218],"survival.":[23],"Hematoxylin":[24],"eosin":[26],"(H&E)":[27],"stained":[28],"slides":[29],"are":[30,143],"widely":[31],"utilized":[32,173],"in":[33,61,72,88,123],"pathology":[34],"for":[35,157,165,185],"tissue":[36,47,92],"staining,":[37],"semantic":[39],"segmentation":[40,188,228],"enables":[41],"precise":[43],"delineation":[44],"various":[46],"components,":[48],"such":[49],"as":[50,174],"cancer":[51],"cells,":[52],"normal":[53],"glands,":[54],"stroma.":[56],"This":[57],"process":[58],"assists":[59],"pathologists":[60],"accurately":[62,84],"identifying":[63],"location,":[65],"extent,":[66],"type":[68],"tissues":[70],"involved":[71],"tumor,":[74],"thereby":[75],"enhancing":[76,161],"accuracy":[78],"efficiency":[80],"diagnosis.":[82],"To":[83],"segment":[85],"glandular":[86],"regions":[87],"H&E-stained":[89],"colorectal":[90,186],"images":[93],"while":[94],"reducing":[95],"computational":[96],"costs,":[97],"this":[98,230],"paper":[99],"proposes":[100],"U-Net":[102],"model":[103,117],"based":[104],"on":[105,180],"multi-axis":[106,152],"focused":[107,153],"attention":[108,154],"randomly":[110,128],"grouped":[111,129],"feature":[112,130,159,167],"aggregation,":[113],"named":[114],"LRG-UNet.":[115],"The":[116],"introduces":[118],"three":[119],"key":[120],"improvements:":[121],"First,":[122],"skip":[125],"connections,":[126],"aggregation":[131],"block":[132],"used":[134],"fuse":[136],"low-level":[137],"features":[138],"at":[139],"each":[140],"stage,":[141],"which":[142],"then":[144],"input":[145],"corresponding":[148],"decoder":[149],"layers.":[150],"Second,":[151],"employed":[156],"global":[158,166],"extraction,":[160],"model\u2019s":[163],"capacity":[164],"modeling.":[168],"Finally,":[169],"deep":[170],"supervision":[171],"training":[176],"strategy.":[177],"Experimental":[178],"results":[179],"public":[182],"GlaS":[183],"dataset":[184],"demonstrate":[189],"that":[190],"algorithm":[192,231],"achieves":[193,232],"Intersection":[194],"over":[195],"Union":[196],"(IoU),":[197],"Dice":[198],"similarity":[199],"coefficient,":[200],"Precision,":[201],"Recall":[203],"$\\mathbf{7":[205,219],"1.":[206],"2":[207,216],"3":[208],"\\%,":[209,212],"~}":[210],"81.84":[211],"\\mathbf{9":[213],"0.":[214],"8":[215],"\\%}$,":[217,223],"8.":[220],"0":[221],"9":[222],"respectively.":[224],"Compared":[225],"other":[227],"methods,":[229],"superior":[233],"performance":[234],"with":[235],"fewer":[236],"parameters.":[237]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}