{"id":"https://openalex.org/W4392747128","doi":"https://doi.org/10.3390/a17030119","title":"A Preprocessing Method for Coronary Artery Stenosis Detection Based on Deep Learning","display_name":"A Preprocessing Method for Coronary Artery Stenosis Detection Based on Deep Learning","publication_year":2024,"publication_date":"2024-03-13","ids":{"openalex":"https://openalex.org/W4392747128","doi":"https://doi.org/10.3390/a17030119"},"language":"en","primary_location":{"id":"doi:10.3390/a17030119","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030119","pdf_url":"https://www.mdpi.com/1999-4893/17/3/119/pdf?version=1710323257","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/17/3/119/pdf?version=1710323257","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011117143","display_name":"Yanjun Li","orcid":"https://orcid.org/0009-0009-0549-2407"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yanjun Li","raw_affiliation_strings":["Graduate School of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan"],"raw_orcid":"https://orcid.org/0009-0009-0549-2407","affiliations":[{"raw_affiliation_string":"Graduate School of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038294668","display_name":"Takaaki Yoshimura","orcid":"https://orcid.org/0000-0002-6663-4335"},"institutions":[{"id":"https://openalex.org/I163793406","display_name":"Health Sciences University of Hokkaido","ror":"https://ror.org/04tqcn816","country_code":"JP","type":"education","lineage":["https://openalex.org/I163793406"]},{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]},{"id":"https://openalex.org/I4210141669","display_name":"Hokkaido University Hospital","ror":"https://ror.org/0419drx70","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210141669"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takaaki Yoshimura","raw_affiliation_strings":["Clinical AI Human Resources Development Program, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","Department of Health Sciences and Technology, Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan","Department of Medical Physics, Hokkaido University Hospital, Sapporo 060-8648, Japan","Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan"],"raw_orcid":"https://orcid.org/0000-0002-6663-4335","affiliations":[{"raw_affiliation_string":"Clinical AI Human Resources Development Program, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","institution_ids":["https://openalex.org/I205349734"]},{"raw_affiliation_string":"Department of Health Sciences and Technology, Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan","institution_ids":["https://openalex.org/I163793406","https://openalex.org/I205349734"]},{"raw_affiliation_string":"Department of Medical Physics, Hokkaido University Hospital, Sapporo 060-8648, Japan","institution_ids":["https://openalex.org/I4210141669"]},{"raw_affiliation_string":"Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076331137","display_name":"Yuto Horima","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuto Horima","raw_affiliation_strings":["Department of Central Radiology, JR Sapporo Hospital, Sapporo 060-0033, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Central Radiology, JR Sapporo Hospital, Sapporo 060-0033, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005534816","display_name":"Hiroyuki Sugimori","orcid":"https://orcid.org/0000-0002-7796-5113"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroyuki Sugimori","raw_affiliation_strings":["Clinical AI Human Resources Development Program, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","Department of Biomedical Science and Engineering, Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan","Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7796-5113","affiliations":[{"raw_affiliation_string":"Clinical AI Human Resources Development Program, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","institution_ids":["https://openalex.org/I205349734"]},{"raw_affiliation_string":"Department of Biomedical Science and Engineering, Faculty of Health Sciences, Hokkaido University, Sapporo 060-0812, Japan","institution_ids":["https://openalex.org/I205349734"]},{"raw_affiliation_string":"Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo 060-8648, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005534816"],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.512,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80188193,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"119","last_page":"119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9975000023841858,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9975000023841858,"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/T10193","display_name":"Coronary Interventions and Diagnostics","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9921000003814697,"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/stenosis","display_name":"Stenosis","score":0.7440761923789978},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7093203067779541},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6707136034965515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6456620693206787},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5387893915176392},{"id":"https://openalex.org/keywords/coronary-artery-disease","display_name":"Coronary artery disease","score":0.5167152285575867},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4758469760417938},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.47184327244758606},{"id":"https://openalex.org/keywords/artery","display_name":"Artery","score":0.46749579906463623},{"id":"https://openalex.org/keywords/coronary-arteries","display_name":"Coronary arteries","score":0.4447936713695526},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4230929911136627},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38176682591438293},{"id":"https://openalex.org/keywords/cardiology","display_name":"Cardiology","score":0.35085588693618774},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3416755795478821}],"concepts":[{"id":"https://openalex.org/C2780007028","wikidata":"https://www.wikidata.org/wiki/Q2343082","display_name":"Stenosis","level":2,"score":0.7440761923789978},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7093203067779541},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6707136034965515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456620693206787},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5387893915176392},{"id":"https://openalex.org/C2778213512","wikidata":"https://www.wikidata.org/wiki/Q844935","display_name":"Coronary artery disease","level":2,"score":0.5167152285575867},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4758469760417938},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.47184327244758606},{"id":"https://openalex.org/C2776820930","wikidata":"https://www.wikidata.org/wiki/Q9655","display_name":"Artery","level":2,"score":0.46749579906463623},{"id":"https://openalex.org/C2778742706","wikidata":"https://www.wikidata.org/wiki/Q18361829","display_name":"Coronary arteries","level":3,"score":0.4447936713695526},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4230929911136627},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38176682591438293},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.35085588693618774},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3416755795478821}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a17030119","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030119","pdf_url":"https://www.mdpi.com/1999-4893/17/3/119/pdf?version=1710323257","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a7e5b28ab5124d139d37f237196a2cc9","is_oa":true,"landing_page_url":"https://doaj.org/article/a7e5b28ab5124d139d37f237196a2cc9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 17, Iss 3, p 119 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a17030119","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030119","pdf_url":"https://www.mdpi.com/1999-4893/17/3/119/pdf?version=1710323257","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G7143781540","display_name":null,"funder_award_id":"JPMJFS2101","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"}],"funders":[{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392747128.pdf"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1984962663","https://openalex.org/W2010965043","https://openalex.org/W2086567618","https://openalex.org/W2114343102","https://openalex.org/W2129534965","https://openalex.org/W2187771232","https://openalex.org/W2407521645","https://openalex.org/W2567511171","https://openalex.org/W2613718673","https://openalex.org/W2782780325","https://openalex.org/W2886584550","https://openalex.org/W2901696962","https://openalex.org/W2917025828","https://openalex.org/W2921910235","https://openalex.org/W2939252810","https://openalex.org/W3007941026","https://openalex.org/W3083282610","https://openalex.org/W3090651641","https://openalex.org/W4377993265","https://openalex.org/W4390099018","https://openalex.org/W6653172889"],"related_works":["https://openalex.org/W2397288865","https://openalex.org/W2401216020","https://openalex.org/W2368524271","https://openalex.org/W2576709312","https://openalex.org/W2079402751","https://openalex.org/W2415915772","https://openalex.org/W2021562513","https://openalex.org/W4383669989","https://openalex.org/W2414481425","https://openalex.org/W2412542586"],"abstract_inverted_index":{"The":[0,108,158],"detection":[1],"of":[2,8,16,37,74,110,145,189],"coronary":[3,17,49,79,125,172],"artery":[4,18,50],"stenosis":[5,21,51,58,77,115],"is":[6,25,82,117,165],"one":[7],"the":[9,14,72,111,121,143,151,162,186,190],"most":[10],"important":[11],"indicators":[12],"for":[13,105,171,193],"diagnosis":[15],"disease.":[19],"However,":[20],"in":[22,78,124],"branch":[23,61,75],"vessels":[24,62],"often":[26,54],"difficult":[27],"to":[28,114,184],"detect":[29,56],"using":[30],"computer-aided":[31],"systems":[32],"and":[33,44,59,99,136,180],"even":[34],"radiologists":[35],"because":[36],"several":[38],"factors,":[39],"such":[40,133],"as":[41,102,134,167],"imaging":[42,156],"angle":[43],"contrast":[45],"agent":[46],"inhomogeneity.":[47],"Traditional":[48],"localization":[52,73],"algorithms":[53],"only":[55],"aortic":[57],"ignore":[60],"that":[63,95,161],"may":[64],"also":[65],"cause":[66],"major":[67],"health":[68],"threats.":[69],"Therefore,":[70],"improving":[71],"vessel":[76,97,195],"angiographic":[80,126,173],"images":[81,152],"a":[83,92,103,168],"potential":[84],"development":[85],"property.":[86],"In":[87],"this":[88],"study,":[89],"we":[90],"propose":[91],"preprocessing":[93,169],"approach":[94],"combines":[96],"enhancement":[98],"image":[100,174],"fusion":[101],"prerequisite":[104],"deep":[106,146,178,191],"learning.":[107],"sensitivity":[109],"neural":[112,131],"network":[113,148],"features":[116,123],"improved":[118],"by":[119],"enhancing":[120],"blurry":[122],"images.":[127],"By":[128],"validating":[129],"five":[130],"networks,":[132],"YOLOv4":[135],"R-FCN-Inceptionresnetv2,":[137],"our":[138],"proposed":[139,163],"method":[140,164,170],"can":[141,181],"improve":[142],"performance":[144],"learning":[147,179],"applications":[149],"on":[150,177],"from":[153],"six":[154],"common":[155],"angles.":[157],"results":[159],"showed":[160],"suitable":[166],"processing":[175],"based":[176],"be":[182],"used":[183],"amend":[185],"recognition":[187],"ability":[188],"model":[192],"fine":[194],"stenosis.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}