{"id":"https://openalex.org/W4224998780","doi":"https://doi.org/10.1109/isbi52829.2022.9761691","title":"Location-Guided Coarse-to-Fine Network for Whole Heart Segmentation","display_name":"Location-Guided Coarse-to-Fine Network for Whole Heart Segmentation","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4224998780","doi":"https://doi.org/10.1109/isbi52829.2022.9761691"},"language":"en","primary_location":{"id":"doi:10.1109/isbi52829.2022.9761691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761691","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100368865","display_name":"Xiang Zhang","orcid":"https://orcid.org/0000-0002-5201-3802"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["Northwest University,School of Information and Technology,China,710127"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwest University,School of Information and Technology,China,710127","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320962","display_name":"Xiao Zhang","orcid":"https://orcid.org/0009-0006-4347-9172"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Zhang","raw_affiliation_strings":["Northwest University,School of Information and Technology,China,710127"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwest University,School of Information and Technology,China,710127","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043852046","display_name":"Hangzai Luo","orcid":"https://orcid.org/0000-0003-3354-5739"},"institutions":[{"id":"https://openalex.org/I37802460","display_name":"Northwest University","ror":"https://ror.org/00z3td547","country_code":"CN","type":"education","lineage":["https://openalex.org/I37802460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangzai Luo","raw_affiliation_strings":["Northwest University,School of Information and Technology,China,710127"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwest University,School of Information and Technology,China,710127","institution_ids":["https://openalex.org/I37802460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101180761","display_name":"Sheng Zhong","orcid":"https://orcid.org/0000-0001-6908-3519"},"institutions":[{"id":"https://openalex.org/I4210089056","display_name":"Beijing Microelectronics Technology Institute","ror":"https://ror.org/007y7ej30","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089056"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Zhong","raw_affiliation_strings":["Xi’an Microelectronics Technology Institute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Microelectronics Technology Institute,China","institution_ids":["https://openalex.org/I4210089056"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064826355","display_name":"Lei Tang","orcid":"https://orcid.org/0000-0001-5465-610X"},"institutions":[{"id":"https://openalex.org/I4210089056","display_name":"Beijing Microelectronics Technology Institute","ror":"https://ror.org/007y7ej30","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210089056"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Tang","raw_affiliation_strings":["Xi’an Microelectronics Technology Institute,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Microelectronics Technology Institute,China","institution_ids":["https://openalex.org/I4210089056"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":null,"first_page":"1","last_page":"5"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9955000281333923,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8081618547439575},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7902223467826843},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.661474347114563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6573442816734314},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5123668909072876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.493659108877182},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.435089647769928},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.418910950422287},{"id":"https://openalex.org/keywords/human-heart","display_name":"Human heart","score":0.4165690243244171},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4154731035232544},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.05826416611671448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8081618547439575},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7902223467826843},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.661474347114563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6573442816734314},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5123668909072876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.493659108877182},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.435089647769928},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.418910950422287},{"id":"https://openalex.org/C2983437453","wikidata":"https://www.wikidata.org/wiki/Q1072","display_name":"Human heart","level":2,"score":0.4165690243244171},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4154731035232544},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.05826416611671448},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi52829.2022.9761691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761691","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1549847950","https://openalex.org/W1903029394","https://openalex.org/W2291593693","https://openalex.org/W2464708700","https://openalex.org/W2792157084","https://openalex.org/W2907750714","https://openalex.org/W2963420686","https://openalex.org/W3004399337","https://openalex.org/W3012147217","https://openalex.org/W3090384914","https://openalex.org/W3126558081","https://openalex.org/W3135360879","https://openalex.org/W3165136712","https://openalex.org/W6743731764","https://openalex.org/W6749046317","https://openalex.org/W6773423673"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W3147584709","https://openalex.org/W4389858081","https://openalex.org/W2737719445","https://openalex.org/W4239098401","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W2977677679","https://openalex.org/W2113201962"],"abstract_inverted_index":{"The":[0],"human":[1],"heart":[2,23,47,57,79,132,136],"is":[3,24,42],"a":[4,34,85,122],"hollow":[5],"muscular":[6],"organ":[7],"with":[8],"very":[9],"large":[10],"variations":[11],"in":[12,80],"shape":[13],"and":[14,17,36,58,113,160],"size,":[15],"automatic":[16,39],"accurate":[18],"segmentation":[19,67,138],"of":[20,55,68,77,95,102,109],"the":[21,52,56,66,74,78,107,110,131,141],"whole":[22,46],"challenging":[25,70],"for":[26,134],"medical":[27],"image":[28],"analysis.":[29],"To":[30],"tackle":[31],"this":[32],"challenge,":[33],"simple":[35],"effective":[37],"fully":[38],"coarse-to-fine":[40],"network":[41],"proposed":[43],"to":[44,64,91,98,164],"enable":[45],"segmentation.":[48],"It":[49],"comprehensively":[50],"captures":[51],"anatomical":[53,75],"dependencies":[54],"its":[59],"substructures":[60,137],"as":[61],"explicit":[62],"guidance":[63],"assist":[65],"these":[69],"substructures.":[71,118],"Based":[72],"on":[73,153],"location":[76],"CT":[81],"slices,":[82,104],"we":[83,120],"design":[84],"Slice":[86],"Channel":[87],"Attention":[88],"(SCA)":[89],"module":[90],"aggregate":[92],"specific":[93],"categories":[94],"response":[96],"channels":[97],"highlight":[99],"feature":[100,143],"representation":[101],"different":[103,117],"thereby":[105],"enhancing":[106],"features":[108],"same":[111],"substructure":[112],"avoiding":[114],"confusion":[115],"between":[116],"Furthermore,":[119],"propose":[121],"Location-aware":[123],"Object":[124],"Generation":[125],"(LOG)":[126],"module,":[127],"which":[128],"can":[129],"generate":[130],"mask":[133],"guiding":[135],"by":[139],"processing":[140],"CNN":[142],"map.":[144],"Experimental":[145],"results":[146],"show":[147],"that":[148],"our":[149,166],"method":[150],"achieves":[151],"state-of-the-art":[152],"MICCAI":[154],"2017":[155],"MM-WHS":[156],"dataset.":[157],"Ablation":[158],"studies":[159],"visualizations":[161],"are":[162],"provided":[163],"understand":[165],"method.":[167]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}