{"id":"https://openalex.org/W2583578793","doi":"https://doi.org/10.1109/tmi.2017.2724070","title":"Constrained Deep Weak Supervision for Histopathology Image Segmentation","display_name":"Constrained Deep Weak Supervision for Histopathology Image Segmentation","publication_year":2017,"publication_date":"2017-07-07","ids":{"openalex":"https://openalex.org/W2583578793","doi":"https://doi.org/10.1109/tmi.2017.2724070","mag":"2583578793","pmid":"https://pubmed.ncbi.nlm.nih.gov/28692971"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2017.2724070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2017.2724070","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1701.00794","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhipeng Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhipeng Jia","raw_affiliation_strings":["Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China","Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xingyi Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyi Huang","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Research Institute of Beihang University in Shenzhen, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Research Institute of Beihang University in Shenzhen, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Eric I-Chao Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Eric I-Chao Chang","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yan Xu","orcid":"https://orcid.org/0000-0002-2636-7594"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Xu","raw_affiliation_strings":["Microsoft Research, Beijing, China","State Key Laboratory of Software Development Environment, Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Research Institute of Beihang University in Shenzhen, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Research Institute of Beihang University in Shenzhen, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210113369","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":11.0166,"has_fulltext":false,"cited_by_count":193,"citation_normalized_percentile":{"value":0.98586222,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"36","issue":"11","first_page":"2376","last_page":"2388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9661999940872192,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9661999940872192,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.007400000002235174,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.0035000001080334187,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6741999983787537},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.554099977016449},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5529000163078308},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5419999957084656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4975000023841858},{"id":"https://openalex.org/keywords/histopathology","display_name":"Histopathology","score":0.44110000133514404},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4316999912261963}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7494999766349792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6829000115394592},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6741999983787537},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.554099977016449},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5529000163078308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5419999957084656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4975000023841858},{"id":"https://openalex.org/C544855455","wikidata":"https://www.wikidata.org/wiki/Q1070952","display_name":"Histopathology","level":2,"score":0.44110000133514404},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3953999876976013},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3917999863624573},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3765999972820282},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.30809998512268066},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2872999906539917}],"mesh":[{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069553","descriptor_name":"Supervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003106","descriptor_name":"Colon","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D003106","descriptor_name":"Colon","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D003106","descriptor_name":"Colon","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D003110","descriptor_name":"Colonic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D003110","descriptor_name":"Colonic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D003110","descriptor_name":"Colonic Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D006651","descriptor_name":"Histocytochemistry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006651","descriptor_name":"Histocytochemistry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006651","descriptor_name":"Histocytochemistry","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","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":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","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":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D046888","descriptor_name":"Tissue Array Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D046888","descriptor_name":"Tissue Array Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D046888","descriptor_name":"Tissue Array Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tmi.2017.2724070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2017.2724070","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:28692971","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28692971","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:arXiv.org:1701.00794","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1701.00794","pdf_url":"https://arxiv.org/pdf/1701.00794","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1701.00794","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1701.00794","pdf_url":"https://arxiv.org/pdf/1701.00794","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G50778745","display_name":null,"funder_award_id":"4152033","funder_id":"https://openalex.org/F4320334977","funder_display_name":"Beijing Municipal Natural Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320308943","display_name":"Microsoft Research","ror":"https://ror.org/00d0nc645"},{"id":"https://openalex.org/F4320334977","display_name":"Beijing Municipal Natural Science Foundation","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W74870555","https://openalex.org/W137456267","https://openalex.org/W845365781","https://openalex.org/W1783315696","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1945608308","https://openalex.org/W1946635378","https://openalex.org/W1975103383","https://openalex.org/W1982390426","https://openalex.org/W2050418754","https://openalex.org/W2072761058","https://openalex.org/W2086749537","https://openalex.org/W2098140880","https://openalex.org/W2101689475","https://openalex.org/W2101771332","https://openalex.org/W2103243046","https://openalex.org/W2107698128","https://openalex.org/W2110119381","https://openalex.org/W2110158442","https://openalex.org/W2117539524","https://openalex.org/W2118246710","https://openalex.org/W2133324800","https://openalex.org/W2135147470","https://openalex.org/W2144349513","https://openalex.org/W2146655125","https://openalex.org/W2156398782","https://openalex.org/W2221898772","https://openalex.org/W2344858100","https://openalex.org/W2406638278","https://openalex.org/W2422982059","https://openalex.org/W2470965540","https://openalex.org/W2521587260","https://openalex.org/W2526942720","https://openalex.org/W2963803174","https://openalex.org/W6631190155","https://openalex.org/W6632200337","https://openalex.org/W6637373629","https://openalex.org/W6640295612","https://openalex.org/W6640383297","https://openalex.org/W6674920064","https://openalex.org/W6675450350","https://openalex.org/W6676245398","https://openalex.org/W6678000420","https://openalex.org/W6683033130","https://openalex.org/W6684369376","https://openalex.org/W6684665197","https://openalex.org/W6726705939"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2159066190","https://openalex.org/W1631910785","https://openalex.org/W2122581818","https://openalex.org/W2110230079","https://openalex.org/W2739874619","https://openalex.org/W2112576502","https://openalex.org/W1988199133","https://openalex.org/W1482124406","https://openalex.org/W1700740617"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,38,64,87],"develop":[4,88],"a":[5,24,31,89,126],"new":[6,32],"weakly":[7,116],"supervised":[8,117],"learning":[9,27,54,68,83,95,131],"algorithm":[10,60],"to":[11,13,44,47,51,92,112,122,129,141,164],"learn":[12],"segment":[14],"cancerous":[15,72],"regions":[16,73],"in":[17,79,109,167],"histopathology":[18,156,171],"images.":[19,179],"This":[20],"paper":[21],"is":[22,84,120,139],"under":[23,96],"multiple":[25],"instance":[26],"(MIL)":[28],"framework":[29],"with":[30,74],"formulation,":[33],"deep":[34],"weak":[35,97],"supervision":[36,98],"(DWS);":[37],"also":[39],"propose":[40],"an":[41,66],"effective":[42],"way":[43],"introduce":[45],"constraints":[46,103],"our":[48,59,110],"neural":[49],"networks":[50,77],"assist":[52],"the":[53,130,151],"process.":[55,132],"The":[56,133],"contributions":[57],"of":[58],"are":[61,107],"threefold:":[62],"1)":[63],"build":[65],"end-to-end":[67],"system":[69,149],"that":[70,119],"segments":[71],"fully":[75],"convolutional":[76],"(FCNs)":[78],"which":[80],"image-to-image":[81],"weakly-supervised":[82],"performed;":[85],"2)":[86],"DWS":[90],"formulation":[91],"exploit":[93],"multi-scale":[94],"within":[99],"FCNs;":[100],"and":[101,124,143,160,177],"3)":[102],"about":[104],"positive":[105],"instances":[106],"introduced":[108],"approach":[111],"effectively":[113],"explore":[114],"additional":[115],"information":[118],"easy":[121,140],"obtain":[123],"enjoy":[125],"significant":[127],"boost":[128],"proposed":[134],"algorithm,":[135],"abbreviated":[136],"as":[137,174],"DWS-MIL,":[138],"implement":[142],"can":[144,161],"be":[145,162],"trained":[146],"efficiently.":[147],"Our":[148],"demonstrates":[150],"state-of-the-art":[152],"results":[153],"on":[154],"large-scale":[155],"image":[157],"data":[158],"sets":[159],"applied":[163],"various":[165],"applications":[166],"medical":[168],"imaging":[169],"beyond":[170],"images,":[172],"such":[173],"MRI,":[175],"CT,":[176],"ultrasound":[178]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":35},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2017-02-10T00:00:00"}