{"id":"https://openalex.org/W4224991227","doi":"https://doi.org/10.1109/isbi52829.2022.9761582","title":"Tgnet: A Task-Guided Network Architecture for Multi-Organ and Tumour Segmentation from Partially Labelled Datasets","display_name":"Tgnet: A Task-Guided Network Architecture for Multi-Organ and Tumour Segmentation from Partially Labelled Datasets","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4224991227","doi":"https://doi.org/10.1109/isbi52829.2022.9761582"},"language":"en","primary_location":{"id":"doi:10.1109/isbi52829.2022.9761582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761582","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th 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/A5100448261","display_name":"Hao Wu","orcid":"https://orcid.org/0000-0003-2853-5034"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Hao Wu","raw_affiliation_strings":["University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088461583","display_name":"Shuchao Pang","orcid":"https://orcid.org/0000-0002-5668-833X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shuchao Pang","raw_affiliation_strings":["University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055952724","display_name":"Arcot Sowmya","orcid":"https://orcid.org/0000-0001-9236-5063"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Arcot Sowmya","raw_affiliation_strings":["University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales,School of Computer Science and Engineering,Sydney,NSW,Australia","institution_ids":["https://openalex.org/I31746571"]},{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100448261"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.8364,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.81284599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9988999962806702,"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/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.8113231658935547},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6669013500213623},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6507024765014648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5921097993850708},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.548328697681427},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.49324506521224976},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.43368351459503174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41617900133132935},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.41144293546676636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3417757749557495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8113231658935547},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6669013500213623},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6507024765014648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5921097993850708},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.548328697681427},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.49324506521224976},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.43368351459503174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41617900133132935},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.41144293546676636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3417757749557495},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi52829.2022.9761582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761582","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2194775991","https://openalex.org/W2526978347","https://openalex.org/W2798122215","https://openalex.org/W2915126261","https://openalex.org/W2929753309","https://openalex.org/W2963452532","https://openalex.org/W2964950992","https://openalex.org/W2986785750","https://openalex.org/W3035367255","https://openalex.org/W3165635828","https://openalex.org/W3176031707","https://openalex.org/W4200160506","https://openalex.org/W6639824700","https://openalex.org/W6750469568","https://openalex.org/W6759274242","https://openalex.org/W6761274798"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W2087343574","https://openalex.org/W4246352526","https://openalex.org/W2121910908"],"abstract_inverted_index":{"The":[0],"cost":[1],"of":[2,14,36,129],"labour":[3],"and":[4,17,116,125,132,142,155,166,198],"expertise":[5],"makes":[6],"it":[7],"challenging":[8],"to":[9,88,105,120,151,170],"collect":[10],"a":[11,23,94,114,138,148],"large":[12],"amount":[13],"medical":[15,20,28],"data":[16],"annotate":[18],"3D":[19],"images":[21],"at":[22],"voxel":[24],"level.":[25],"Most":[26],"public":[27],"datasets":[29,180],"are":[30,65,145],"only":[31,47],"labelled":[32,51,72,202],"with":[33,191],"one":[34],"type":[35],"organ":[37],"or":[38,92],"tumour.":[39],"For":[40],"example,":[41],"in":[42,70,147,194],"the":[43,48,54,171],"liver":[44,49],"segmentation":[45,173],"task,":[46],"is":[50],"while":[52],"all":[53,98],"other":[55],"organs,":[56],"even":[57],"when":[58],"present,":[59],"as":[60,62,67],"well":[61],"irrelevant":[63],"parts":[64],"annotated":[66],"background,":[68],"resulting":[69],"partially":[71,201],"datasets.":[73],"Current":[74],"popular":[75],"methods":[76],"usually":[77],"build":[78],"multiple":[79,196],"neural":[80],"network":[81,96,118],"models":[82],"for":[83,97],"different":[84,130,135],"tasks":[85,99],"that":[86,182],"lead":[87],"great":[89],"model":[90,185],"redundancy,":[91],"design":[93],"unified":[95,115],"which":[100],"suffers":[101],"from":[102,134,200],"low":[103],"ability":[104],"extract":[106],"task-related":[107,123],"features.":[108],"In":[109],"this":[110],"paper,":[111],"we":[112],"propose":[113],"task-guided":[117,149,184],"architecture":[119],"efficiently":[121],"learn":[122],"features":[124,154,165,168],"avoid":[126],"mixing":[127],"representations":[128],"organs":[131,197],"tumours":[133,199],"tasks.":[136],"Specifically,":[137],"novel":[139],"residual":[140],"block":[141],"attention":[143],"module":[144],"devised":[146],"way":[150],"fuse":[152],"image":[153],"task":[156],"encoding":[157],"constraints.":[158],"Moreover,":[159],"both":[160],"designs":[161],"significantly":[162],"suppress":[163],"task-unrelated":[164],"highlight":[167],"related":[169],"specific":[172],"task.":[174],"Experiments":[175],"conducted":[176],"on":[177],"seven":[178],"benchmark":[179],"illustrate":[181],"our":[183],"achieves":[186],"more":[187],"competitive":[188],"performance":[189],"compared":[190],"state-of-the-art":[192],"approaches":[193],"segmenting":[195],"data.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
