{"id":"https://openalex.org/W3011929037","doi":"https://doi.org/10.1117/12.2548496","title":"3D U-Net for segmentation of pulmonary nodules in volumetric CT scans from multi-annotator truth estimation","display_name":"3D U-Net for segmentation of pulmonary nodules in volumetric CT scans from multi-annotator truth estimation","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3011929037","doi":"https://doi.org/10.1117/12.2548496","mag":"3011929037"},"language":"en","primary_location":{"id":"doi:10.1117/12.2548496","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2548496","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","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/A5035918473","display_name":"William Funke","orcid":null},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"William Funke","raw_affiliation_strings":["Univ. of Louisville (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Louisville (United States)","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036581178","display_name":"Benjamin Veasey","orcid":null},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Veasey","raw_affiliation_strings":["Univ. of Louisville (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Louisville (United States)","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015925094","display_name":"Jacek M. \u017burada","orcid":"https://orcid.org/0000-0001-6622-534X"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacek Zurada","raw_affiliation_strings":["Univ. of Louisville (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Louisville (United States)","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044691751","display_name":"Hichem Frigui","orcid":"https://orcid.org/0000-0002-8281-1629"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hichem Frigui","raw_affiliation_strings":["Univ. of Louisville (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Louisville (United States)","institution_ids":["https://openalex.org/I142740786"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005411439","display_name":"Amir A. Amini","orcid":"https://orcid.org/0000-0001-9698-8989"},"institutions":[{"id":"https://openalex.org/I142740786","display_name":"University of Louisville","ror":"https://ror.org/01ckdn478","country_code":"US","type":"education","lineage":["https://openalex.org/I142740786"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir A. Amini","raw_affiliation_strings":["Univ. of Louisville (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Louisville (United States)","institution_ids":["https://openalex.org/I142740786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035918473"],"corresponding_institution_ids":["https://openalex.org/I142740786"],"apc_list":null,"apc_paid":null,"fwci":0.63,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71864076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"78","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9980999827384949,"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":0.9980999827384949,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9962000250816345,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9883000254631042,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7609883546829224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7508566975593567},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6602323055267334},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6457901000976562},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.6145374774932861},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.567154586315155},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5605195164680481},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5277267694473267},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5025992393493652},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4875485301017761},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.4615841507911682},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43596577644348145},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.41014406085014343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.396415650844574},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.2782738506793976},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25476670265197754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10242325067520142},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08830901980400085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7609883546829224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7508566975593567},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6602323055267334},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6457901000976562},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.6145374774932861},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.567154586315155},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5605195164680481},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5277267694473267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5025992393493652},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4875485301017761},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.4615841507911682},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43596577644348145},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.41014406085014343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.396415650844574},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2782738506793976},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25476670265197754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10242325067520142},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08830901980400085},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2548496","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2548496","pdf_url":null,"source":{"id":"https://openalex.org/S4306519512","display_name":"Medical Imaging 2020: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8899999856948853,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4389060404","https://openalex.org/W2973136608","https://openalex.org/W3012828488","https://openalex.org/W4286233748","https://openalex.org/W2046969815","https://openalex.org/W4254054209","https://openalex.org/W4200334192","https://openalex.org/W2086489015","https://openalex.org/W2952835238","https://openalex.org/W4313044406"],"abstract_inverted_index":{"Low":[0],"dose":[1],"CT":[2,110,146],"screening":[3],"has":[4,41,94],"been":[5,96],"shown":[6,42],"to":[7,13,22,43,62,80,89,103,133,163,232],"significantly":[8],"reduce":[9],"mortality":[10],"rates":[11],"due":[12],"lung":[14,33],"cancer.":[15],"To":[16],"assist":[17],"radiologists,":[18],"CAD":[19],"systems":[20],"continue":[21],"be":[23,44,186],"developed":[24],"for":[25,46,84,130,139],"automatically":[26],"detecting,":[27],"segmenting,":[28],"and":[29,58,75,83,100,109,127],"categorizing":[30],"potentially":[31],"malignant":[32],"nodules.":[34],"Deep":[35],"learning":[36],"with":[37,159,222],"the":[38,66,78,149,202,207],"U-Net":[39,225],"architecture":[40],"effective":[45],"automatic":[47,220],"segmentation":[48,221],"of":[49,55,87,175],"2-D":[50],"images.":[51],"The":[52],"network":[53,79],"consists":[54],"a":[56,134,193,197,223],"down-sampling":[57,74],"up-sampling":[59],"path,":[60],"similar":[61],"an":[63],"auto-encoder.":[64],"However,":[65],"concept":[67,93],"driving":[68],"its":[69],"success":[70],"is":[71,179],"skip-connections":[72],"between":[73,188,238],"up-sampling,":[76],"allowing":[77],"preserve":[81],"details":[82],"easier":[85],"backpropagation":[86],"error":[88],"deep":[90],"layers.":[91],"This":[92,112,152,190],"previously":[95],"brought":[97],"into":[98],"3-D":[99,135,224],"successfully":[101],"applied":[102],"image":[104,142],"volumes":[105],"such":[106],"as":[107],"MRI":[108],"scans.":[111],"paper":[113,191,213],"applies":[114],"concepts":[115],"from":[116,148,156,161,201],"these":[117,176],"works":[118],"(skip":[119],"connections,":[120],"batch":[121],"normalization,":[122],"Dice":[123],"similarity":[124,230,236],"coefficient":[125],"loss,":[126],"stride":[128],"convolution":[129],"down":[131],"sampling)":[132],"Convolutional":[136],"Neural":[137],"Network":[138],"segmenting":[140],"nodule":[141],"patches":[143],"in":[144,211,228],"thoracic":[145],"scans":[147,155],"LIDC-IDRI":[150],"database.":[151],"database":[153],"contains":[154],"1018":[157],"cases":[158],"annotations":[160,205],"up":[162],"4":[164],"human":[165,233,239],"experts.":[166,177],"Within":[167],"each":[168,174],"scan,":[169],"nodules":[170],"are":[171],"delineated":[172],"by":[173],"It":[178],"well":[180],"known":[181],"that":[182,215],"manual":[183],"delineation":[184],"can":[185,226],"subjective":[187],"annotators.":[189,240],"proposes":[192],"model":[194],"trained":[195,217],"on":[196,218],"ground":[198],"truth":[199],"estimation":[200],"four":[203],"expert":[204],"using":[206],"STAPLE":[208],"algorithm.":[209],"Experiments":[210],"this":[212],"show":[214],"when":[216],"STAPLE,":[219],"result":[227],"improved":[229],"scores":[231,237],"annotators":[234],"than":[235]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}