{"id":"https://openalex.org/W3012115094","doi":"https://doi.org/10.1117/12.2549812","title":"Learning numerical observers using unsupervised domain adaptation","display_name":"Learning numerical observers using unsupervised domain adaptation","publication_year":2020,"publication_date":"2020-03-16","ids":{"openalex":"https://openalex.org/W3012115094","doi":"https://doi.org/10.1117/12.2549812","mag":"3012115094"},"language":"en","primary_location":{"id":"doi:10.1117/12.2549812","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment","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/A5101429467","display_name":"Shenghua He","orcid":"https://orcid.org/0000-0003-3944-7662"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shenghua He","raw_affiliation_strings":["Washington Univ. in St. Louis (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington Univ. in St. Louis (United States)","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035698435","display_name":"Weimin Zhou","orcid":"https://orcid.org/0000-0001-6678-4088"},"institutions":[{"id":"https://openalex.org/I204465549","display_name":"Washington University in St. Louis","ror":"https://ror.org/01yc7t268","country_code":"US","type":"education","lineage":["https://openalex.org/I204465549"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weimin Zhou","raw_affiliation_strings":["Washington Univ. in St. Louis (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington Univ. in St. Louis (United States)","institution_ids":["https://openalex.org/I204465549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057105337","display_name":"Hua Li","orcid":"https://orcid.org/0000-0002-5629-2247"},"institutions":[{"id":"https://openalex.org/I1308343090","display_name":"Carle Foundation Hospital","ror":"https://ror.org/02nfcgd30","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1308343090"]},{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hua Li","raw_affiliation_strings":["Carle Cancer Ctr., Carle Foundation Hospital (United States)","Univ. of Illinois at Urbana-Champaign (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carle Cancer Ctr., Carle Foundation Hospital (United States)","institution_ids":["https://openalex.org/I1308343090"]},{"raw_affiliation_string":"Univ. of Illinois at Urbana-Champaign (United States)","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046506193","display_name":"Mark A. Anastasio","orcid":"https://orcid.org/0000-0002-3192-4172"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Anastasio","raw_affiliation_strings":["Univ. of Illinois at Urbana-Champaign (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Illinois at Urbana-Champaign (United States)","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6678,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66673232,"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":"30","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9484000205993652,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.9484000205993652,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9442999958992004,"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":0.9282000064849854,"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":0.7645918130874634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7612701058387756},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6127879023551941},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5560876727104187},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5389007329940796},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5112833976745605},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5063410997390747},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5053256154060364},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4890766739845276},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4723801612854004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4595138132572174},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44731834530830383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4360790550708771},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12002000212669373},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.10723736882209778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645918130874634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7612701058387756},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6127879023551941},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5560876727104187},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5389007329940796},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5112833976745605},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5063410997390747},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5053256154060364},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4890766739845276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4723801612854004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4595138132572174},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44731834530830383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4360790550708771},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12002000212669373},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.10723736882209778},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2549812","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2990774877","https://openalex.org/W3093339210"],"abstract_inverted_index":{"Medical":[0],"imaging":[1,78],"systems":[2],"are":[3,156],"commonly":[4],"assessed":[5],"by":[6],"use":[7,128,184],"of":[8,33,76,103,111,129,140,200,211,217,220],"objective":[9],"image":[10,26,50,82,94,147,178,187,229],"quality":[11,27],"measures.":[12],"Supervised":[13],"deep":[14,38,150],"learning":[15],"methods":[16],"have":[17],"been":[18],"investigated":[19],"to":[20,36,46,56,65,98,116,135,163],"implement":[21],"numerical":[22,152],"observers":[23,153],"for":[24,149,183,192],"task-based":[25],"assessment.":[28],"However,":[29],"labeling":[30],"large":[31],"amounts":[32],"experimental":[34,93,146,164,186,195,228],"data":[35,51,83,95,148,179,230],"train":[37],"neural":[39],"networks":[40],"is":[41,62,114,207,231],"tedious,":[42],"expensive,":[43],"and":[44,73,88,125,145,180,227],"prone":[45],"subjective":[47],"errors.":[48],"Computer-simulated":[49],"can":[52],"potentially":[53],"be":[54,174],"employed":[55],"circumvent":[57],"these":[58,106],"issues;":[59],"however,":[60],"it":[61],"often":[63],"difficult":[64],"computationally":[66],"model":[67],"complicated":[68],"anatomical":[69],"structures,":[70],"noise":[71],"sources,":[72],"the":[74,92,101,109,127,137,167,190,218,225],"response":[75],"real-world":[77],"systems.":[79],"Hence,":[80],"simulated":[81,144,159,226],"will":[84,172],"generally":[85],"possess":[86],"physical":[87],"statistical":[89],"differences":[90,107],"from":[91],"they":[96],"seek":[97],"emulate.":[99],"Within":[100],"context":[102],"machine":[104],"learning,":[105],"between":[108,143,224],"sets":[110],"two":[112],"images":[113,160],"referred":[115],"as":[117,214],"<i>domain":[118],"shift</i>.":[119],"In":[120,166],"this":[121,212],"study,":[122],"we":[123],"propose":[124],"investigate":[126],"an":[130],"adversarial":[131],"domain":[132,141,221],"adaptation":[133],"method":[134],"mitigate":[136],"deleterious":[138],"effects":[139],"shift":[142,222],"learning-based":[151],"(DL-NOs)":[154],"that":[155],"trained":[157,175],"on":[158,176],"but":[161],"applied":[162],"ones.":[165],"proposed":[168],"method,":[169],"a":[170,198,202,215],"DL-NO":[171],"initially":[173],"computer-simulated":[177],"subsequently":[181],"adapted":[182],"with":[185],"data,":[188],"without":[189],"need":[191],"any":[193],"labeled":[194],"images.":[196],"As":[197],"proof":[199],"concept,":[201],"binary":[203],"signal":[204],"detection":[205],"task":[206],"considered.":[208],"The":[209],"success":[210],"strategy":[213],"function":[216],"degree":[219],"present":[223],"investigated.":[232]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}