{"id":"https://openalex.org/W3153987619","doi":"https://doi.org/10.1109/tmi.2021.3139161","title":"A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation","display_name":"A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation","publication_year":2021,"publication_date":"2021-12-30","ids":{"openalex":"https://openalex.org/W3153987619","doi":"https://doi.org/10.1109/tmi.2021.3139161","mag":"3153987619","pmid":"https://pubmed.ncbi.nlm.nih.gov/34965206"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2021.3139161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3139161","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9786024/09664634.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/42/9786024/09664634.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Minh H. Vu","orcid":"https://orcid.org/0000-0002-2391-1419"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Minh H. Vu","raw_affiliation_strings":["Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-2391-1419","affiliations":[{"raw_affiliation_string":"Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gabriella Norman","orcid":null},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Gabriella Norman","raw_affiliation_strings":["Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tufve Nyholm","orcid":"https://orcid.org/0000-0002-8971-9788"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Tufve Nyholm","raw_affiliation_strings":["Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-8971-9788","affiliations":[{"raw_affiliation_string":"Department of Radiation Sciences, Radiation Physics, Ume&#x00E5; University, Ume&#x00E5;, Sweden","institution_ids":["https://openalex.org/I90267481"]}]},{"author_position":"last","author":{"id":null,"display_name":"Tommy Lofstedt","orcid":"https://orcid.org/0000-0001-7119-7646"},"institutions":[{"id":"https://openalex.org/I90267481","display_name":"Ume\u00e5 University","ror":"https://ror.org/05kb8h459","country_code":"SE","type":"education","lineage":["https://openalex.org/I90267481"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Tommy Lofstedt","raw_affiliation_strings":["Department of Computing Science, Ume&#x00E5; University, Ume&#x00E5;, Sweden"],"raw_orcid":"https://orcid.org/0000-0001-7119-7646","affiliations":[{"raw_affiliation_string":"Department of Computing Science, Ume&#x00E5; University, Ume&#x00E5;, Sweden","institution_ids":["https://openalex.org/I90267481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7762,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.7301979,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"41","issue":"6","first_page":"1320","last_page":"1330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.3596999943256378,"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":0.3596999943256378,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.10700000077486038,"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/T10862","display_name":"AI in cancer detection","score":0.07760000228881836,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7149999737739563},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6654000282287598},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5332000255584717},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49219998717308044},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48089998960494995},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4713999927043915},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4697999954223633},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.462799996137619},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.45750001072883606},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44620001316070557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7940000295639038},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7149999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7129999995231628},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6654000282287598},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5357000231742859},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5332000255584717},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49219998717308044},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4697999954223633},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.462799996137619},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.45750001072883606},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44620001316070557},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.40549999475479126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40070000290870667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3928000032901764},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3905999958515167},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32919999957084656},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26330000162124634},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26190000772476196},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.2513999938964844}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003952","descriptor_name":"Diagnostic Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2021.3139161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3139161","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9786024/09664634.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:34965206","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34965206","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on medical imaging","raw_type":null},{"id":"pmh:oai:DiVA.org:umu-191280","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-191280","pdf_url":null,"source":{"id":"https://openalex.org/S4306400361","display_name":"DiVA at Ume\u00e5 University (Ume\u00e5 University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I90267481","host_organization_name":"Ume\u00e5 University","host_organization_lineage":["https://openalex.org/I90267481"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1109/tmi.2021.3139161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tmi.2021.3139161","pdf_url":"https://ieeexplore.ieee.org/ielx7/42/9786024/09664634.pdf","source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1364868472","display_name":null,"funder_award_id":"2018-05973","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"},{"id":"https://openalex.org/G3321450376","display_name":null,"funder_award_id":"05973","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"},{"id":"https://openalex.org/G633570985","display_name":null,"funder_award_id":"2018-05973","funder_id":"https://openalex.org/F4320322971","funder_display_name":"Ume\u00e5 Universitet"},{"id":"https://openalex.org/G712881263","display_name":null,"funder_award_id":"2018-","funder_id":"https://openalex.org/F4320322581","funder_display_name":"Vetenskapsr\u00e5det"},{"id":"https://openalex.org/G761683401","display_name":null,"funder_award_id":"AMP 20-1027","funder_id":"https://openalex.org/F4320322972","funder_display_name":"Cancer Research Foundation in Northern Sweden"},{"id":"https://openalex.org/G8767225864","display_name":null,"funder_award_id":"LP 18-2182","funder_id":"https://openalex.org/F4320322972","funder_display_name":"Cancer Research Foundation in Northern Sweden"}],"funders":[{"id":"https://openalex.org/F4320322581","display_name":"Vetenskapsr\u00e5det","ror":"https://ror.org/03zttf063"},{"id":"https://openalex.org/F4320322971","display_name":"Ume\u00e5 Universitet","ror":"https://ror.org/05kb8h459"},{"id":"https://openalex.org/F4320322972","display_name":"Cancer Research Foundation in Northern Sweden","ror":"https://ror.org/05kb8h459"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3153987619.pdf","grobid_xml":"https://content.openalex.org/works/W3153987619.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1565746575","https://openalex.org/W1901129140","https://openalex.org/W1936750108","https://openalex.org/W2005940465","https://openalex.org/W2089683684","https://openalex.org/W2331464089","https://openalex.org/W2464708700","https://openalex.org/W2533800772","https://openalex.org/W2569480018","https://openalex.org/W2751665805","https://openalex.org/W2891155035","https://openalex.org/W2921629474","https://openalex.org/W2929508119","https://openalex.org/W2962914239","https://openalex.org/W2963043051","https://openalex.org/W2963717741","https://openalex.org/W2979492442","https://openalex.org/W2982043723","https://openalex.org/W2995193676","https://openalex.org/W2999484173","https://openalex.org/W3128646645","https://openalex.org/W3140422664","https://openalex.org/W4253187718","https://openalex.org/W6676179485","https://openalex.org/W6677088747","https://openalex.org/W6678911119","https://openalex.org/W6761785670"],"related_works":[],"abstract_inverted_index":{"In":[0,141],"the":[1,9,32,78,88,119,127,137,142,168,187,224,236,241],"last":[2],"years,":[3],"deep":[4,23,47],"learning":[5,24,197],"has":[6],"dramatically":[7],"improved":[8],"performances":[10],"in":[11,40,43,77,116,171,194,247],"a":[12,108,147,218],"variety":[13],"of":[14,22,55,75,121,210,243],"medical":[15,44,79],"image":[16,56,80],"analysis":[17],"applications.":[18],"Among":[19],"different":[20],"types":[21],"models,":[25,232],"convolutional":[26,48],"neural":[27,49],"networks":[28,50],"have":[29,37,132,181],"been":[30,38],"among":[31],"most":[33],"successful":[34],"and":[35,69,87,115,159,239],"they":[36,214],"used":[39],"many":[41],"applications":[42],"imaging.":[45],"Training":[46],"often":[51,67],"requires":[52],"large":[53,73,219],"amounts":[54,74],"data":[57,76,170],"to":[58,61,71,83,92,133,151,167,173,206],"generalize":[59],"well":[60,193],"new":[62,103,128,211],"unseen":[63],"images.":[64],"It":[65],"is":[66,112,124,203],"time-consuming":[68],"expensive":[70,84],"collect":[72],"domain":[81],"due":[82],"imaging":[85],"systems,":[86],"need":[89],"for":[90],"experts":[91],"manually":[93],"make":[94],"ground":[95],"truth":[96],"annotations.":[97,183],"A":[98],"potential":[99],"problem":[100],"arises":[101],"if":[102],"structures":[104,129],"are":[105],"added":[106],"when":[107,179,213],"decision":[109,138],"support":[110,139],"system":[111],"already":[113],"deployed":[114],"use.":[117],"Since":[118],"field":[120],"radiation":[122],"therapy":[123],"constantly":[125],"developing,":[126],"would":[130],"also":[131,191],"be":[134],"covered":[135],"by":[136],"system.":[140],"present":[143],"work,":[144],"we":[145],"propose":[146],"novel":[148],"loss":[149,164,189],"function":[150,165,190],"solve":[152],"multiple":[153,245],"problems:":[154],"imbalanced":[155],"datasets,":[156],"partially-labeled":[157],"data,":[158,177],"incremental":[160,196],"learning.":[161],"The":[162],"proposed":[163,188,225],"adapts":[166],"available":[169,176],"order":[172],"utilize":[174],"all":[175],"even":[178],"some":[180],"missing":[182],"We":[184],"demonstrate":[185],"that":[186,223],"works":[192],"an":[195,200],"setting,":[198],"where":[199],"existing":[201],"model":[202],"easily":[204],"adapted":[205],"semi-automatically":[207],"incorporate":[208],"delineations":[209],"organs":[212],"appear.":[215],"Experiments":[216],"on":[217,228],"in-house":[220],"dataset":[221],"show":[222],"method":[226],"performs":[227],"par":[229],"with":[230],"baseline":[231],"while":[233],"greatly":[234],"reducing":[235],"training":[237],"time":[238],"eliminating":[240],"hassle":[242],"maintaining":[244],"models":[246],"practice.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2021-04-26T00:00:00"}
