{"id":"https://openalex.org/W4205239084","doi":"https://doi.org/10.1109/bigdata52589.2021.9671847","title":"Generalization in Cardiac Image Segmentation","display_name":"Generalization in Cardiac Image Segmentation","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205239084","doi":"https://doi.org/10.1109/bigdata52589.2021.9671847"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671847","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"2021 IEEE International Conference on Big Data (Big Data)","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/A5100525424","display_name":"Zhengjie Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengjie Xu","raw_affiliation_strings":["Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101546895","display_name":"Zixiang Zhou","orcid":"https://orcid.org/0000-0002-4409-2029"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zixiang Zhou","raw_affiliation_strings":["Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005315243","display_name":"Garrison W. Cottrell","orcid":"https://orcid.org/0000-0001-7538-1715"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Garrison W. Cottrell","raw_affiliation_strings":["Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, University of California, San Diego, La Jolla, CA, U.S.A","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102154730","display_name":"Mai H. Nguyen","orcid":"https://orcid.org/0000-0002-4945-1334"},"institutions":[{"id":"https://openalex.org/I181653535","display_name":"San Diego Supercomputer Center","ror":"https://ror.org/04mg3nk07","country_code":"US","type":"facility","lineage":["https://openalex.org/I181653535","https://openalex.org/I36258959"]},{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mai H. Nguyen","raw_affiliation_strings":["San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, U.S.A"],"affiliations":[{"raw_affiliation_string":"San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA, U.S.A","institution_ids":["https://openalex.org/I181653535","https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100525424"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15596198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"51","issue":null,"first_page":"2838","last_page":"2847"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9975000023841858,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9975000023841858,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9968000054359436,"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/generalization","display_name":"Generalization","score":0.8358097076416016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7992044687271118},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7526226043701172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7361985445022583},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6671321988105774},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6235656142234802},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5738449096679688},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5738334655761719},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.559452474117279},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.511942982673645},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5045892000198364},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.48079147934913635},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4302177131175995},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4233900308609009},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.41763490438461304},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3386826515197754},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05809128284454346},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05763569474220276}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.8358097076416016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7992044687271118},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7526226043701172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7361985445022583},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6671321988105774},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6235656142234802},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5738449096679688},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5738334655761719},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.559452474117279},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.511942982673645},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5045892000198364},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.48079147934913635},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4302177131175995},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4233900308609009},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.41763490438461304},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3386826515197754},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05809128284454346},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05763569474220276},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671847","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W2009921846","https://openalex.org/W2057441779","https://openalex.org/W2095905764","https://openalex.org/W2109906982","https://openalex.org/W2153475545","https://openalex.org/W2154549868","https://openalex.org/W2187887962","https://openalex.org/W2337438617","https://openalex.org/W2606437410","https://openalex.org/W2606576226","https://openalex.org/W2741891296","https://openalex.org/W2804047627","https://openalex.org/W2883606943","https://openalex.org/W2919434187","https://openalex.org/W2960736282","https://openalex.org/W2962807789","https://openalex.org/W2962885625","https://openalex.org/W2963150697","https://openalex.org/W2964043069","https://openalex.org/W2964212292","https://openalex.org/W3009563704","https://openalex.org/W4205182665","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6747605639"],"related_works":["https://openalex.org/W2130553454","https://openalex.org/W3022007134","https://openalex.org/W4317548404","https://openalex.org/W2087783760","https://openalex.org/W1509924131","https://openalex.org/W3104108945","https://openalex.org/W2033364610","https://openalex.org/W3163689946","https://openalex.org/W4287890939","https://openalex.org/W2797776314"],"abstract_inverted_index":{"Deep":[0],"learning":[1,18,104],"methods":[2],"have":[3],"achieved":[4],"great":[5],"success":[6],"in":[7,50],"medical":[8,21],"imaging":[9,22],"applications.":[10],"Although":[11],"data":[12,66,72],"is":[13,24],"very":[14],"crucial":[15],"for":[16,40,102],"deep":[17,103],"models,":[19],"the":[20,27,83,98],"domain":[23],"restricted":[25],"by":[26],"limited":[28],"size":[29],"of":[30,64,85],"datasets":[31,45,59],"and":[32,46,90],"differences":[33],"between":[34],"them.":[35],"This":[36],"makes":[37],"it":[38],"difficult":[39],"models":[41,105],"to":[42,56,61,96,106],"generalize":[43],"across":[44,110],"achieve":[47,107],"robust":[48],"performance":[49,69],"practical":[51],"settings.":[52],"Therefore,":[53],"knowing":[54],"how":[55],"combine":[57],"different":[58,93,111],"together":[60],"take":[62],"advantage":[63],"new":[65],"while":[67],"retaining":[68],"on":[70,82],"previous":[71],"becomes":[73],"an":[74],"important":[75],"problem.":[76],"In":[77],"this":[78],"paper,":[79],"we":[80],"focus":[81],"task":[84],"cardiac":[86],"image":[87],"semantic":[88],"segmentation":[89],"synthesize":[91],"five":[92],"real-world":[94],"scenarios":[95],"find":[97],"optimal":[99],"training":[100],"approach":[101],"good":[108],"generalization":[109],"datasets.":[112]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}