{"id":"https://openalex.org/W3019726275","doi":"https://doi.org/10.1109/isbi45749.2020.9098566","title":"Zero-Shot Medical Image Artifact Reduction","display_name":"Zero-Shot Medical Image Artifact Reduction","publication_year":2020,"publication_date":"2020-04-01","ids":{"openalex":"https://openalex.org/W3019726275","doi":"https://doi.org/10.1109/isbi45749.2020.9098566","mag":"3019726275"},"language":"en","primary_location":{"id":"doi:10.1109/isbi45749.2020.9098566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th 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/A5100731677","display_name":"Yu-Jen Chen","orcid":"https://orcid.org/0000-0002-0908-3522"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Jen Chen","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111475056","display_name":"Yen\u2010Jung Chang","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yen-Jung Chang","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079256723","display_name":"Shao-Cheng Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shao-Cheng Wen","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000141831","display_name":"Yiyu Shi","orcid":"https://orcid.org/0000-0002-6788-9823"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyu Shi","raw_affiliation_strings":["University of Notre Dame, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071529609","display_name":"Xiaowei Xu","orcid":"https://orcid.org/0000-0002-1046-6379"},"institutions":[{"id":"https://openalex.org/I2799425052","display_name":"Guangdong General Hospital","ror":"https://ror.org/03jpekd50","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2799425052"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Xu","raw_affiliation_strings":["Guangdong General Hospital, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong General Hospital, China","institution_ids":["https://openalex.org/I2799425052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062800747","display_name":"Tsung-Yi Ho","orcid":"https://orcid.org/0000-0001-7348-5625"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Yi Ho","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101142935","display_name":"Qianjun Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I2799425052","display_name":"Guangdong General Hospital","ror":"https://ror.org/03jpekd50","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2799425052"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianjun Jia","raw_affiliation_strings":["Guangdong General Hospital, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong General Hospital, China","institution_ids":["https://openalex.org/I2799425052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003562224","display_name":"Meiping Huang","orcid":"https://orcid.org/0000-0002-0745-852X"},"institutions":[{"id":"https://openalex.org/I2799425052","display_name":"Guangdong General Hospital","ror":"https://ror.org/03jpekd50","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2799425052"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiping Huang","raw_affiliation_strings":["Guangdong General Hospital, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong General Hospital, China","institution_ids":["https://openalex.org/I2799425052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029085468","display_name":"Jian Zhuang","orcid":"https://orcid.org/0000-0003-0142-4238"},"institutions":[{"id":"https://openalex.org/I2799425052","display_name":"Guangdong General Hospital","ror":"https://ror.org/03jpekd50","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I2799425052"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhuang","raw_affiliation_strings":["Guangdong General Hospital, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong General Hospital, China","institution_ids":["https://openalex.org/I2799425052"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.8636,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.97170958,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"862","last_page":"866"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9976000189781189,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9919000267982483,"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/artifact","display_name":"Artifact (error)","score":0.7786242961883545},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7762407064437866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7658435106277466},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6007122993469238},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5215975046157837},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.513517439365387},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5123237371444702},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5098451972007751},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.492917537689209},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4703060984611511},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.46212100982666016},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.42714279890060425},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4229535758495331},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4179506301879883},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12017950415611267}],"concepts":[{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.7786242961883545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7762407064437866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7658435106277466},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6007122993469238},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5215975046157837},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.513517439365387},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5123237371444702},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5098451972007751},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.492917537689209},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4703060984611511},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.46212100982666016},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.42714279890060425},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4229535758495331},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4179506301879883},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12017950415611267},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi45749.2020.9098566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi45749.2020.9098566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1812490466","https://openalex.org/W1990130348","https://openalex.org/W2010999467","https://openalex.org/W2067018983","https://openalex.org/W2101891472","https://openalex.org/W2137577808","https://openalex.org/W2144536070","https://openalex.org/W2508982726","https://openalex.org/W2617128058","https://openalex.org/W2743780012","https://openalex.org/W2748739903","https://openalex.org/W2771305881","https://openalex.org/W2777741489","https://openalex.org/W2784007680","https://openalex.org/W2887746098","https://openalex.org/W2947746588","https://openalex.org/W2963503375","https://openalex.org/W2963948425","https://openalex.org/W2964013315","https://openalex.org/W2964121744","https://openalex.org/W2979542579","https://openalex.org/W2979579242","https://openalex.org/W3011945959","https://openalex.org/W3104724358","https://openalex.org/W6631943919","https://openalex.org/W6680683657","https://openalex.org/W6769035001"],"related_works":["https://openalex.org/W52840052","https://openalex.org/W3162837891","https://openalex.org/W1687852313","https://openalex.org/W3029243869","https://openalex.org/W2502336004","https://openalex.org/W1741504538","https://openalex.org/W4308623176","https://openalex.org/W2019696434","https://openalex.org/W2358078963","https://openalex.org/W2023249001"],"abstract_inverted_index":{"Medical":[0],"images":[1,165],"may":[2],"contain":[3],"various":[4],"types":[5],"of":[6,74,96,150],"artifacts":[7,109,133,162],"with":[8,43],"different":[9],"patterns":[10],"and":[11,48,99,120,140],"mixtures,":[12],"which":[13,70],"depend":[14],"on":[15],"many":[16],"factors":[17],"such":[18],"as":[19,125],"scan":[20],"setting,":[21],"machine":[22],"condition,":[23],"patients'":[24],"characteristics,":[25],"surrounding":[26],"environment,":[27],"etc.":[28],"However,":[29],"existing":[30],"deep":[31,75,157],"learning":[32,76,158],"based":[33],"artifact":[34,46,104],"reduction":[35,105],"methods":[36],"are":[37],"restricted":[38],"by":[39],"their":[40],"training":[41,170],"set":[42],"specific":[44],"predetermined":[45],"type":[47],"pattern.":[49],"As":[50],"such,":[51],"they":[52],"have":[53],"limited":[54],"clinical":[55],"adoption.":[56],"In":[57],"this":[58,153],"paper,":[59],"we":[60,89],"introduce":[61],"a":[62,101,168],"\u201cZero-Shot\u201d":[63],"medical":[64,164],"image":[65,86,98,112],"Artifact":[66],"Reduction":[67],"(ZSAR)":[68],"framework,":[69],"leverages":[71],"the":[72,91,136,148,155],"power":[73],"but":[77],"without":[78,166],"using":[79,143,167],"general":[80],"pre-trained":[81],"networks":[82],"or":[83],"any":[84],"clean":[85],"reference.":[87],"Specifically,":[88],"utilize":[90],"low":[92],"internal":[93],"visual":[94],"entropy":[95],"an":[97,111],"train":[100],"light-weight":[102],"image-specific":[103],"network":[106],"to":[107,127],"reduce":[108,132],"in":[110,163],"at":[113],"test-time.":[114],"We":[115],"use":[116],"Computed":[117],"Tomography":[118],"(CT)":[119],"Magnetic":[121],"Resonance":[122],"Imaging":[123],"(MRI)":[124],"vehicles":[126],"show":[128],"that":[129,160],"ZSAR":[130],"can":[131],"better":[134],"than":[135],"state-of-the-art":[137],"both":[138],"qualitatively":[139],"quantitatively,":[141],"while":[142],"shorter":[144],"test":[145],"time.":[146],"To":[147],"best":[149],"our":[151],"knowledge,":[152],"is":[154],"first":[156],"framework":[159],"reduces":[161],"priori":[169],"set.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
