{"id":"https://openalex.org/W4399868613","doi":"https://doi.org/10.3389/fcomp.2024.1386514","title":"Weakly supervised pre-training for brain tumor segmentation using principal axis measurements of tumor burden","display_name":"Weakly supervised pre-training for brain tumor segmentation using principal axis measurements of tumor burden","publication_year":2024,"publication_date":"2024-06-20","ids":{"openalex":"https://openalex.org/W4399868613","doi":"https://doi.org/10.3389/fcomp.2024.1386514"},"language":"en","primary_location":{"id":"doi:10.3389/fcomp.2024.1386514","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2024.1386514","pdf_url":"https://www.frontiersin.org/articles/10.3389/fcomp.2024.1386514/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/fcomp.2024.1386514/pdf?isPublishedV2=False","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092340400","display_name":"Joshua Edward Mckone","orcid":null},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Joshua E. Mckone","raw_affiliation_strings":["School of Computer Science, University of Lincoln, Lincoln, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln, Lincoln, United Kingdom","institution_ids":["https://openalex.org/I51532219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007414647","display_name":"Tryphon Lambrou","orcid":"https://orcid.org/0000-0003-2899-5815"},"institutions":[{"id":"https://openalex.org/I195460627","display_name":"University of Aberdeen","ror":"https://ror.org/016476m91","country_code":"GB","type":"education","lineage":["https://openalex.org/I195460627"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tryphon Lambrou","raw_affiliation_strings":["School of Natural and Computing Sciences, King's College, University of Aberdeen, Aberdeen, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Natural and Computing Sciences, King's College, University of Aberdeen, Aberdeen, United Kingdom","institution_ids":["https://openalex.org/I195460627"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037392936","display_name":"Xujiong Ye","orcid":"https://orcid.org/0000-0003-0115-0724"},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xujiong Ye","raw_affiliation_strings":["School of Computer Science, University of Lincoln, Lincoln, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln, Lincoln, United Kingdom","institution_ids":["https://openalex.org/I51532219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013498181","display_name":"James M. Brown","orcid":"https://orcid.org/0000-0001-7636-4554"},"institutions":[{"id":"https://openalex.org/I51532219","display_name":"University of Lincoln","ror":"https://ror.org/03yeq9x20","country_code":"GB","type":"education","lineage":["https://openalex.org/I51532219"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James M. Brown","raw_affiliation_strings":["School of Computer Science, University of Lincoln, Lincoln, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Lincoln, Lincoln, United Kingdom","institution_ids":["https://openalex.org/I51532219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5092340400"],"corresponding_institution_ids":["https://openalex.org/I51532219"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":0.3658,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61709524,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"6","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9995999932289124,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9986000061035156,"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/principal","display_name":"Principal (computer security)","score":0.6179922819137573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5901892781257629},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5680023431777954},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5499847531318665},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4698849022388458},{"id":"https://openalex.org/keywords/principal-axis-theorem","display_name":"Principal axis theorem","score":0.4684840440750122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43035823106765747},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4013174772262573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3460497260093689},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3358212113380432},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2561403810977936},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.21073570847511292},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07144740223884583}],"concepts":[{"id":"https://openalex.org/C144559511","wikidata":"https://www.wikidata.org/wiki/Q2986279","display_name":"Principal (computer security)","level":2,"score":0.6179922819137573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5901892781257629},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5680023431777954},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5499847531318665},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4698849022388458},{"id":"https://openalex.org/C161326058","wikidata":"https://www.wikidata.org/wiki/Q7245073","display_name":"Principal axis theorem","level":2,"score":0.4684840440750122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43035823106765747},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4013174772262573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3460497260093689},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3358212113380432},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2561403810977936},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.21073570847511292},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07144740223884583},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fcomp.2024.1386514","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2024.1386514","pdf_url":"https://www.frontiersin.org/articles/10.3389/fcomp.2024.1386514/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:aura.abdn.ac.uk:2164/24046","is_oa":false,"landing_page_url":"https://hdl.handle.net/2164/24046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400966","display_name":"Aberdeen University Research Archive (Aberdeen University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I195460627","host_organization_name":"University of Aberdeen","host_organization_lineage":["https://openalex.org/I195460627"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal article"},{"id":"pmh:oai:doaj.org/article:039675d2777349f2ae4644033eb1410f","is_oa":false,"landing_page_url":"https://doaj.org/article/039675d2777349f2ae4644033eb1410f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Computer Science, Vol 6 (2024)","raw_type":"article"},{"id":"pmh:oai:figshare.com:article/25967203","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Weakly_supervised_pre-training_for_brain_tumor_segmentation_using_principal_axis_measurements_of_tumor_burden/25967203","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3389/fcomp.2024.1386514","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fcomp.2024.1386514","pdf_url":"https://www.frontiersin.org/articles/10.3389/fcomp.2024.1386514/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210211086","display_name":"Frontiers in Computer Science","issn_l":"2624-9898","issn":["2624-9898"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399868613.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1641498739","https://openalex.org/W1986649315","https://openalex.org/W2141619730","https://openalex.org/W2275232108","https://openalex.org/W2751069891","https://openalex.org/W2805605684","https://openalex.org/W2883683269","https://openalex.org/W2899663142","https://openalex.org/W2900298334","https://openalex.org/W2901166159","https://openalex.org/W2916850088","https://openalex.org/W2929508119","https://openalex.org/W2951141079","https://openalex.org/W3003728293","https://openalex.org/W3011974116","https://openalex.org/W3013085919","https://openalex.org/W3098637688","https://openalex.org/W3104205547","https://openalex.org/W3109789186","https://openalex.org/W4220820843","https://openalex.org/W4225529241","https://openalex.org/W4226202507","https://openalex.org/W4286792124","https://openalex.org/W4287815264","https://openalex.org/W4311767714","https://openalex.org/W4385874203","https://openalex.org/W6639824700","https://openalex.org/W6752671361","https://openalex.org/W6752932445","https://openalex.org/W6776305959","https://openalex.org/W6787129766"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W230091440","https://openalex.org/W2126145365","https://openalex.org/W2036609560","https://openalex.org/W2022188753","https://openalex.org/W2361329093","https://openalex.org/W4250644203"],"abstract_inverted_index":{"Introduction":[0],"State-of-the-art":[1],"multi-modal":[2,61],"brain":[3,62],"tumor":[4,63,113,137],"segmentation":[5],"methods":[6],"often":[7],"rely":[8],"on":[9],"large":[10],"quantities":[11],"of":[12,57,90,170],"manually":[13],"annotated":[14],"data":[15,25,40],"to":[16,72,87,97,164],"produce":[17],"acceptable":[18],"results.":[19],"In":[20],"settings":[21],"where":[22],"such":[23,44,58],"labeled":[24],"may":[26,30],"be":[27,31],"scarce,":[28],"there":[29],"value":[32],"in":[33,48,174],"exploiting":[34],"cheaper":[35],"or":[36],"more":[37,182],"readily":[38],"available":[39],"through":[41],"clinical":[42],"trials,":[43],"as":[45,131],"Response":[46],"Assessment":[47],"Neuro-Oncology":[49],"(RANO).":[50],"Methods":[51],"This":[52],"study":[53],"demonstrates":[54],"the":[55,91,101,107,159,175],"utility":[56],"measurements":[59,76],"for":[60,129,135,178],"segmentation,":[64],"whereby":[65],"an":[66],"encoder":[67,108,121,147],"network":[68],"is":[69],"first":[70],"trained":[71,120,153,163],"regress":[73],"synthetic":[74],"\u201cPseudo-RANO\u201d":[75],"using":[77],"a":[78,125,132],"mean":[79],"squared":[80],"error":[81],"loss":[82],"with":[83,100,116,124,185],"cosine":[84],"similarity":[85],"penalty":[86],"promote":[88],"orthogonality":[89],"principal":[92,114],"axes.":[93],"Using":[94],"oriented":[95],"bounding-boxes":[96],"measure":[98],"overlap":[99],"ground":[102,189],"truth,":[103],"we":[104],"show":[105],"that":[106,144],"model":[109],"can":[110],"reliably":[111],"estimate":[112],"axes":[115],"good":[117],"performance.":[118],"The":[119,168],"was":[122],"combined":[123],"randomly":[126],"initialized":[127],"decoder":[128],"fine-tuning":[130],"U-Net":[133],"architecture":[134],"whole":[136],"(WT)":[138],"segmentation.":[139,166],"Results":[140],"Our":[141],"results":[142],"demonstrate":[143],"weakly":[145],"supervised":[146],"models":[148],"converge":[149],"faster":[150,180],"than":[151],"those":[152],"without":[154],"pre-training":[155],"and":[156,181],"help":[157],"minimize":[158],"annotation":[160],"burden":[161],"when":[162],"perform":[165],"Discussion":[167],"use":[169],"cheap,":[171],"low-fidelity":[172],"labels":[173],"context":[176],"allows":[177],"both":[179],"stable":[183],"training":[184],"fewer":[186],"densely":[187],"segmented":[188],"truth":[190],"masks,":[191],"which":[192],"has":[193],"potential":[194],"uses":[195],"outside":[196],"this":[197],"particular":[198],"paradigm.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
