{"id":"https://openalex.org/W4393379132","doi":"https://doi.org/10.1002/ima.23070","title":"A hybrid convolutional and transformer network for segmentation of coronary computed tomography angiographic slices","display_name":"A hybrid convolutional and transformer network for segmentation of coronary computed tomography angiographic slices","publication_year":2024,"publication_date":"2024-04-01","ids":{"openalex":"https://openalex.org/W4393379132","doi":"https://doi.org/10.1002/ima.23070"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1002/ima.23070","pdf_url":null,"source":{"id":"https://openalex.org/S15952048","display_name":"International Journal of Imaging Systems and Technology","issn_l":"0899-9457","issn":["0899-9457","1098-1098"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5033777406","display_name":"Xiaojie Duan","orcid":"https://orcid.org/0000-0001-9088-1646"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tianjin Polytechnic University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaojie Duan","raw_affiliation_strings":["Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078513085","display_name":"Yanchao Wang","orcid":"https://orcid.org/0009-0009-0559-4462"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tianjin Polytechnic University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanchao Wang","raw_affiliation_strings":["Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100707504","display_name":"Jianming Wang","orcid":"https://orcid.org/0000-0002-6235-1362"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tianjin Polytechnic University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Wang","raw_affiliation_strings":["Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems, School of Electronics and Information Engineering, Tiangong University, Tianjin, China","institution_ids":["https://openalex.org/I198091727"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5033777406"],"corresponding_institution_ids":["https://openalex.org/I198091727"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450,"provenance":"doaj"},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":84},"biblio":{"volume":"34","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9969,"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":0.9969,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9918,"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":0.9833,"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":[],"concepts":[{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.6623137},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.63076043},{"id":"https://openalex.org/C3019004856","wikidata":"https://www.wikidata.org/wiki/Q42297149","display_name":"Coronary angiography","level":3,"score":0.49804854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46623465},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.445045},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.43654603},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42671862},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.4242366},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.39504233},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.3130831},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1776478},{"id":"https://openalex.org/C500558357","wikidata":"https://www.wikidata.org/wiki/Q12152","display_name":"Myocardial infarction","level":2,"score":0.10396114},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1002/ima.23070","pdf_url":null,"source":{"id":"https://openalex.org/S15952048","display_name":"International Journal of Imaging Systems and Technology","issn_l":"0899-9457","issn":["0899-9457","1098-1098"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.69}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"62072335"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61872269"},{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"61903273"},{"funder":"https://openalex.org/F4320336756","funder_display_name":"Tianjin Science and Technology Program","award_id":"19PTZWHZ00020"}],"datasets":[],"versions":[],"referenced_works_count":28,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W2003426268","https://openalex.org/W2011767487","https://openalex.org/W2194775991","https://openalex.org/W2793422020","https://openalex.org/W2884585870","https://openalex.org/W2964309882","https://openalex.org/W3034552520","https://openalex.org/W3131500599","https://openalex.org/W3138516171","https://openalex.org/W3168491317","https://openalex.org/W3170841864","https://openalex.org/W3217483830","https://openalex.org/W4214634256","https://openalex.org/W4221020680","https://openalex.org/W4240543907","https://openalex.org/W4285506640","https://openalex.org/W4295934721","https://openalex.org/W4296425595","https://openalex.org/W4312794844","https://openalex.org/W4312950730","https://openalex.org/W4319300975","https://openalex.org/W4321232185","https://openalex.org/W4377011942","https://openalex.org/W4379116850","https://openalex.org/W4380537929","https://openalex.org/W4385252058"],"related_works":["https://openalex.org/W4389858081","https://openalex.org/W4385583601","https://openalex.org/W4379231730","https://openalex.org/W4366343436","https://openalex.org/W4324315429","https://openalex.org/W4298131179","https://openalex.org/W3204400600","https://openalex.org/W2799953226","https://openalex.org/W2501551404","https://openalex.org/W2113201962"],"abstract_inverted_index":{"Abstract":[0],"Coronary":[1],"artery":[2,29,41,87,159,185],"three\u2010dimensional":[3,166],"reconstruction":[4,167],"is":[5,67],"essential":[6],"for":[7,24,85],"preventing,":[8],"diagnosing,":[9],"and":[10,74,81,146,181],"treating":[11],"coronary":[12,28,40,86,128,158,170,184],"heart":[13],"disease.":[14],"This":[15],"study":[16],"introduces":[17],"SegUnet,":[18],"a":[19,47,52,118,173],"lightweight":[20],"hybrid":[21],"CNN\u2010Transformer":[22],"network":[23,134],"pixel\u2010level":[25],"segmentation":[26,160],"of":[27,39,121,127,148,155,165,168,179,183],"computed":[30],"tomography":[31],"angiography":[32],"(CTA)":[33],"slices":[34],"to":[35,60,77,91,101],"enhance":[36],"the":[37,58,65,124,133,143,163,169,177],"precision":[38],"reconstruction.":[42],"The":[43,152],"overall":[44],"SegUnet":[45,116,156],"adopts":[46],"U\u2010shaped":[48],"encoder\u2010decoder":[49],"structure,":[50],"with":[51,69],"hierarchical":[53],"Transformer":[54],"structure":[55,76],"serving":[56],"as":[57],"encoder":[59,106],"extract":[61],"global":[62],"contextual":[63],"information;":[64],"decoder":[66],"enhanced":[68],"spatial":[70],"attention":[71],"mechanism":[72],"(SAM)":[73],"residual":[75],"improve":[78],"its":[79],"perception":[80],"adaptive":[82],"adjustment":[83],"abilities":[84],"vessels.":[88],"In":[89],"contrast":[90],"other":[92],"methods,":[93],"we":[94],"propose":[95],"an":[96],"interpolation\u2010based":[97],"multi\u2010feature":[98],"fusion":[99],"bridge":[100],"integrate":[102],"multi\u2010scale":[103],"features":[104],"between":[105],"levels,":[107],"capturing":[108],"their":[109],"semantic":[110],"dependencies.":[111],"Experimental":[112],"results":[113],"show":[114],"that":[115],"achieves":[117],"prediction":[119],"accuracy":[120],"97.23%":[122],"on":[123,138,176],"test":[125],"set":[126],"arteries":[129],"2D":[130],"slices.":[131],"Moreover,":[132],"exhibits":[135],"excellent":[136],"performance":[137,154],"Synapse":[139],"Multi\u2010Organ":[140],"Segmentation,":[141],"highlighting":[142],"superiority,":[144],"effectiveness,":[145],"robustness":[147],"our":[149],"proposed":[150],"method.":[151],"outstanding":[153],"in":[157],"has":[161],"elevated":[162],"quality":[164],"arteries,":[171],"exerting":[172],"positive":[174],"impact":[175],"enhancement":[178],"diagnosis":[180],"treatment":[182],"diseases.":[186]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4393379132","counts_by_year":[],"updated_date":"2024-12-06T21:23:32.397646","created_date":"2024-04-02"}