{"id":"https://openalex.org/W3164451689","doi":"https://doi.org/10.1109/isbi48211.2021.9433985","title":"Multi-Task Semi-Supervised Learning For Pulmonary Lobe Segmentation","display_name":"Multi-Task Semi-Supervised Learning For Pulmonary Lobe Segmentation","publication_year":2021,"publication_date":"2021-04-13","ids":{"openalex":"https://openalex.org/W3164451689","doi":"https://doi.org/10.1109/isbi48211.2021.9433985","mag":"3164451689"},"language":"en","primary_location":{"id":"doi:10.1109/isbi48211.2021.9433985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9433985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th 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/A5015067399","display_name":"Jingnan Jia","orcid":"https://orcid.org/0000-0002-1025-2557"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Jingnan Jia","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066061437","display_name":"Zhiwei Zhai","orcid":"https://orcid.org/0000-0002-4016-6000"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Zhiwei Zhai","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040038561","display_name":"Margreet Bakker","orcid":"https://orcid.org/0000-0002-3803-3380"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"M. Els Bakker","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059683611","display_name":"Irene Hern\u00e1ndez\u2010Gir\u00f3n","orcid":"https://orcid.org/0000-0002-2235-098X"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"I. Hernandez-Giron","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025788902","display_name":"Marius Staring","orcid":"https://orcid.org/0000-0003-2885-5812"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Marius Staring","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056059876","display_name":"Berend C. Stoel","orcid":"https://orcid.org/0000-0002-5975-8559"},"institutions":[{"id":"https://openalex.org/I2800006345","display_name":"Leiden University Medical Center","ror":"https://ror.org/05xvt9f17","country_code":"NL","type":"funder","lineage":["https://openalex.org/I2800006345"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Berend C. Stoel","raw_affiliation_strings":["Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Division of Image Processing, Leiden University Medical Center (LUMC), P.O. Box 9600, Leiden, RC, The Netherlands","institution_ids":["https://openalex.org/I2800006345"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015067399"],"corresponding_institution_ids":["https://openalex.org/I2800006345"],"apc_list":null,"apc_paid":null,"fwci":0.437,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63968603,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1329","last_page":"1332"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9696000218391418,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9225000143051147,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/computer-science","display_name":"Computer science","score":0.8309297561645508},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7220582962036133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7114408612251282},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7060956358909607},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6493729948997498},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.5805754661560059},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5793378949165344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4941284954547882},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4573201537132263},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41457661986351013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8309297561645508},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7220582962036133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7114408612251282},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7060956358909607},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6493729948997498},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.5805754661560059},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5793378949165344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4941284954547882},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4573201537132263},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41457661986351013},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi48211.2021.9433985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9433985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.41999998688697815}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2149799076","https://openalex.org/W2333102131","https://openalex.org/W2342450965","https://openalex.org/W2584017349","https://openalex.org/W2887477052","https://openalex.org/W2897447732","https://openalex.org/W2929753309","https://openalex.org/W2947556306","https://openalex.org/W2949133717","https://openalex.org/W2962914239","https://openalex.org/W2963282853","https://openalex.org/W2979651795","https://openalex.org/W6702435863","https://openalex.org/W6761274798"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2397288865","https://openalex.org/W2611989081","https://openalex.org/W2368524271","https://openalex.org/W2576709312","https://openalex.org/W4230611425","https://openalex.org/W2787993192","https://openalex.org/W2731899572","https://openalex.org/W2392797073","https://openalex.org/W2989490741"],"abstract_inverted_index":{"Pulmonary":[0],"lobe":[1,37],"segmentation":[2],"is":[3,55,103,148],"an":[4,116],"important":[5],"preprocessing":[6],"task":[7],"for":[8,150],"the":[9,26,107,112,132],"analysis":[10],"of":[11,28,60,86],"lung":[12],"diseases.":[13],"Traditional":[14],"methods":[15,42],"relying":[16],"on":[17,115],"fissure":[18],"detection":[19],"or":[20],"other":[21],"anatomical":[22],"features,":[23],"such":[24,66],"as":[25,154],"distribution":[27],"pulmonary":[29],"vessels":[30],"and":[31,92],"airways,":[32],"could":[33],"provide":[34],"reasonably":[35],"accurate":[36],"segmentations.":[38],"Deep":[39,52],"learning":[40,54],"based":[41],"can":[43,83],"outperform":[44],"these":[45],"traditional":[46],"approaches,":[47],"but":[48],"require":[49],"large":[50],"datasets.":[51,72],"multi-task":[53],"expected":[56],"to":[57,105,139],"utilize":[58],"labels":[59,67],"multiple":[61,71,87],"different":[62,96,108,151],"structures.":[63,97],"However,":[64],"commonly":[65],"are":[68],"distributed":[69],"over":[70],"In":[73],"this":[74],"paper,":[75],"we":[76],"proposed":[77],"a":[78],"multitask":[79],"semi-supervised":[80],"model":[81,114,126],"that":[82,124,145],"leverage":[84],"information":[85],"structures":[88],"from":[89,136],"unannotated":[90],"datasets":[91,93],"annotated":[94],"with":[95],"A":[98],"focused":[99],"alternating":[100],"training":[101],"strategy":[102],"presented":[104],"balance":[106],"tasks.":[109],"We":[110,142],"evaluated":[111],"trained":[113],"external":[117],"independent":[118],"CT":[119],"dataset.":[120],"The":[121],"results":[122],"show":[123],"our":[125,146],"significantly":[127],"outperforms":[128],"single-task":[129],"alternatives,":[130],"improving":[131],"mean":[133],"surface":[134],"distance":[135],"7.174":[137],"mm":[138],"4.196":[140],"mm.":[141],"also":[143],"demonstrated":[144],"approach":[147],"successful":[149],"network":[152],"architectures":[153],"backbones.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
