{"id":"https://openalex.org/W2948730003","doi":"https://doi.org/10.1109/jbhi.2020.2986926","title":"Multi-Scale Self-Guided Attention for Medical Image Segmentation","display_name":"Multi-Scale Self-Guided Attention for Medical Image Segmentation","publication_year":2020,"publication_date":"2020-04-14","ids":{"openalex":"https://openalex.org/W2948730003","doi":"https://doi.org/10.1109/jbhi.2020.2986926","mag":"2948730003","pmid":"https://pubmed.ncbi.nlm.nih.gov/32305947"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2020.2986926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2020.2986926","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1906.02849","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101586019","display_name":"Ashish Sinha","orcid":"https://orcid.org/0000-0003-1395-6629"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Sinha","raw_affiliation_strings":["Indian Institute of Technology Roorkee, Roorkee, India","INDIAN INSTITUTE OF TECHNOLOGY ROORKEE"],"raw_orcid":"https://orcid.org/0000-0003-1395-6629","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee, Roorkee, India","institution_ids":["https://openalex.org/I154851008"]},{"raw_affiliation_string":"INDIAN INSTITUTE OF TECHNOLOGY ROORKEE","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004770604","display_name":"Jos\u00e9 Dolz","orcid":"https://orcid.org/0000-0002-2436-7750"},"institutions":[{"id":"https://openalex.org/I9736820","display_name":"\u00c9cole de Technologie Sup\u00e9rieure","ror":"https://ror.org/0020snb74","country_code":"CA","type":"education","lineage":["https://openalex.org/I49663120","https://openalex.org/I9736820"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jose Dolz","raw_affiliation_strings":["\u00c9cole de technologie Superieure, Montreal, QC, Canada","Ecole de technologie sup\u00e9rieure"],"raw_orcid":"https://orcid.org/0000-0002-2436-7750","affiliations":[{"raw_affiliation_string":"\u00c9cole de technologie Superieure, Montreal, QC, Canada","institution_ids":["https://openalex.org/I9736820"]},{"raw_affiliation_string":"Ecole de technologie sup\u00e9rieure","institution_ids":["https://openalex.org/I9736820"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.831,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.85685717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"25","issue":"1","first_page":"121","last_page":"130"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9998000264167786,"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/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"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":0.7864712476730347},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6943625807762146},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6504662036895752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6157729029655457},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5822706818580627},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5548238158226013},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5330691933631897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5326606631278992},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5123151540756226},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4418632686138153},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4323304295539856},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3967410922050476}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7864712476730347},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6943625807762146},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6504662036895752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6157729029655457},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5822706818580627},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5548238158226013},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5330691933631897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5326606631278992},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5123151540756226},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4418632686138153},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4323304295539856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3967410922050476},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[{"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":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":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}],"locations_count":6,"locations":[{"id":"doi:10.1109/jbhi.2020.2986926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2020.2986926","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"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 Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:32305947","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32305947","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 journal of biomedical and health informatics","raw_type":null},{"id":"pmh:oai:arXiv.org:1906.02849","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.02849","pdf_url":"https://arxiv.org/pdf/1906.02849","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":"","raw_type":"text"},{"id":"mag:2948730003","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1906.02849","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:espace2.etsmtl.ca:22195","is_oa":false,"landing_page_url":"http://espace2.etsmtl.ca/id/eprint/22195/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402392","display_name":"Espace \u00c9TS (ETS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1341030882","host_organization_name":"Educational Testing Service","host_organization_lineage":["https://openalex.org/I1341030882"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article publi\u00e9 dans une revue, r\u00e9vis\u00e9 par les pairs"},{"id":"doi:10.48550/arxiv.1906.02849","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1906.02849","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1906.02849","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1906.02849","pdf_url":"https://arxiv.org/pdf/1906.02849","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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2948730003.pdf","grobid_xml":"https://content.openalex.org/works/W2948730003.grobid-xml"},"referenced_works_count":70,"referenced_works":["https://openalex.org/W1156767201","https://openalex.org/W1641498739","https://openalex.org/W1817277359","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1938976761","https://openalex.org/W1948751323","https://openalex.org/W1987291471","https://openalex.org/W2039466015","https://openalex.org/W2104276184","https://openalex.org/W2110158442","https://openalex.org/W2266059378","https://openalex.org/W2412782625","https://openalex.org/W2413794162","https://openalex.org/W2526009326","https://openalex.org/W2550553598","https://openalex.org/W2560023338","https://openalex.org/W2560645892","https://openalex.org/W2563705555","https://openalex.org/W2567599812","https://openalex.org/W2592929672","https://openalex.org/W2598666589","https://openalex.org/W2751069891","https://openalex.org/W2759084104","https://openalex.org/W2799142782","https://openalex.org/W2804047627","https://openalex.org/W2804142894","https://openalex.org/W2821427990","https://openalex.org/W2884555738","https://openalex.org/W2885218528","https://openalex.org/W2886934227","https://openalex.org/W2888358068","https://openalex.org/W2891451067","https://openalex.org/W2891511539","https://openalex.org/W2895340641","https://openalex.org/W2903642350","https://openalex.org/W2913629396","https://openalex.org/W2913736247","https://openalex.org/W2914410118","https://openalex.org/W2936801852","https://openalex.org/W2950893734","https://openalex.org/W2955058313","https://openalex.org/W2962677366","https://openalex.org/W2962781062","https://openalex.org/W2962891704","https://openalex.org/W2963091558","https://openalex.org/W2963403868","https://openalex.org/W2963495494","https://openalex.org/W2963606038","https://openalex.org/W2963606198","https://openalex.org/W2963730812","https://openalex.org/W2963794428","https://openalex.org/W2963840672","https://openalex.org/W2963903399","https://openalex.org/W2963954913","https://openalex.org/W2964105113","https://openalex.org/W2964227007","https://openalex.org/W2964309882","https://openalex.org/W2979777575","https://openalex.org/W2997225633","https://openalex.org/W3103805449","https://openalex.org/W3104390926","https://openalex.org/W6638480814","https://openalex.org/W6639824700","https://openalex.org/W6684665197","https://openalex.org/W6696085341","https://openalex.org/W6739901393","https://openalex.org/W6748481559","https://openalex.org/W6751733626","https://openalex.org/W6755891590"],"related_works":["https://openalex.org/W2798122215","https://openalex.org/W1901129140","https://openalex.org/W3114814504","https://openalex.org/W3182372246","https://openalex.org/W2194775991","https://openalex.org/W3094865497","https://openalex.org/W3000055254","https://openalex.org/W2777623412","https://openalex.org/W3082775802","https://openalex.org/W2981526348","https://openalex.org/W3096627121","https://openalex.org/W2965014217","https://openalex.org/W3016830346","https://openalex.org/W2951727050","https://openalex.org/W3176976503","https://openalex.org/W2996699350","https://openalex.org/W2901249224","https://openalex.org/W2981335848","https://openalex.org/W2948636084","https://openalex.org/W1903029394"],"abstract_inverted_index":{"Even":[0],"though":[1],"convolutional":[2],"neural":[3],"networks":[4,189],"(CNNs)":[5],"are":[6,39,50],"driving":[7],"progress":[8],"in":[9,55,111,149,178],"medical":[10,222],"image":[11,138],"segmentation,":[12],"standard":[13,205],"models":[14],"still":[15],"have":[16],"some":[17],"drawbacks.":[18],"First,":[19],"the":[20,75,85,116,123,137,146,150,172,179,197,200,204,209],"use":[21,32,86],"of":[22,33,87,136,152,168,174,199,211,221],"multi-scale":[23],"approaches,":[24],"i.e.,":[25],"encoder-decoder":[26],"architectures,":[27],"leads":[28],"to":[29,70,95,126,185,214],"a":[30],"redundant":[31],"information,":[34],"where":[35],"similar":[36],"low-level":[37],"features":[38,98],"extracted":[40],"multiple":[41,44],"times":[42],"at":[43],"scales.":[45],"Second,":[46],"long-range":[47],"feature":[48,58,142],"dependencies":[49,82],"not":[51],"efficiently":[52],"modeled,":[53],"resulting":[54],"non-optimal":[56],"discriminative":[57],"representations":[59],"associated":[60],"with":[61,74,99],"each":[62],"semantic":[63,153],"class.":[64],"In":[65,182],"this":[66],"paper":[67],"we":[68],"attempt":[69],"overcome":[71],"these":[72,175],"limitations":[73],"proposed":[76,147,180],"architecture,":[77],"by":[78,139],"capturing":[79],"richer":[80],"contextual":[81],"based":[83],"on":[84,132,155],"guided":[88],"self-attention":[89],"mechanisms.":[90],"This":[91,207],"approach":[92,213],"is":[93,226],"able":[94],"integrate":[96],"local":[97],"their":[100],"corresponding":[101],"global":[102],"dependencies,":[103],"as":[104,106],"well":[105],"highlight":[107],"interdependent":[108],"channel":[109],"maps":[110],"an":[112],"adaptive":[113],"manner.":[114],"Further,":[115],"additional":[117],"loss":[118],"between":[119],"different":[120,157],"modules":[121,177],"guides":[122],"attention":[124,176],"mechanisms":[125],"neglect":[127],"irrelevant":[128],"information":[129],"and":[130,163,217],"focus":[131],"more":[133],"discriminant":[134],"regions":[135],"emphasizing":[140],"relevant":[141],"associations.":[143],"We":[144],"evaluate":[145],"model":[148,191],"context":[151],"segmentation":[154,188,194],"three":[156],"datasets:":[158],"abdominal":[159],"organs,":[160],"cardiovascular":[161],"structures":[162],"brain":[164],"tumors.":[165],"A":[166],"series":[167],"ablation":[169],"experiments":[170],"support":[171],"importance":[173],"architecture.":[181],"addition,":[183],"compared":[184],"other":[186],"state-of-the-art":[187],"our":[190,212],"yields":[192],"better":[193],"performance,":[195],"increasing":[196],"accuracy":[198],"predictions":[201],"while":[202],"reducing":[203],"deviation.":[206],"demonstrates":[208],"efficiency":[210],"generate":[215],"precise":[216],"reliable":[218],"automatic":[219],"segmentations":[220],"images.":[223],"Our":[224],"code":[225],"made":[227],"publicly":[228],"available":[229],"at:":[230],"https://github.com/sinAshish/Multi-Scale-Attention.":[231]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}