{"id":"https://openalex.org/W4294975680","doi":"https://doi.org/10.1109/embc48229.2022.9870993","title":"Dilated Convolution ResNet with Boosting Attention Modules and Combined Loss Functions for LDCT Image Denoising","display_name":"Dilated Convolution ResNet with Boosting Attention Modules and Combined Loss Functions for LDCT Image Denoising","publication_year":2022,"publication_date":"2022-07-11","ids":{"openalex":"https://openalex.org/W4294975680","doi":"https://doi.org/10.1109/embc48229.2022.9870993","pmid":"https://pubmed.ncbi.nlm.nih.gov/36086586"},"language":"en","primary_location":{"id":"doi:10.1109/embc48229.2022.9870993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9870993","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","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 44th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5049477587","display_name":"Luella Marcos","orcid":"https://orcid.org/0000-0003-0728-2904"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Luella Marcos","raw_affiliation_strings":["Ryerson Univeristy,Department of Electrical and Computer Engineering,Toronto,ON,Canada,M5B2K3"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ryerson Univeristy,Department of Electrical and Computer Engineering,Toronto,ON,Canada,M5B2K3","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026782796","display_name":"Franz Quint","orcid":"https://orcid.org/0000-0002-8757-6883"},"institutions":[{"id":"https://openalex.org/I70886390","display_name":"Karlsruhe University of Applied Sciences","ror":"https://ror.org/01c0m1t63","country_code":"DE","type":"education","lineage":["https://openalex.org/I70886390"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Franz Quint","raw_affiliation_strings":["Hochschule Karlsruhe University of Applied Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Karlsruhe University of Applied Sciences","institution_ids":["https://openalex.org/I70886390"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017986343","display_name":"Paul Babyn","orcid":"https://orcid.org/0000-0001-8965-7305"},"institutions":[{"id":"https://openalex.org/I2801053234","display_name":"Royal University Hospital","ror":"https://ror.org/00wg2b048","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I23625684","https://openalex.org/I2801053234"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Paul Babyn","raw_affiliation_strings":["University of Saskatoon Health Region, Royal University Hospital,Department of Medical Imaging,Saskatoon,SK,Canada,S7N0W8"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Saskatoon Health Region, Royal University Hospital,Department of Medical Imaging,Saskatoon,SK,Canada,S7N0W8","institution_ids":["https://openalex.org/I2801053234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086896369","display_name":"Javad Alirezaie","orcid":"https://orcid.org/0000-0001-7129-4825"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Javad Alirezaie","raw_affiliation_strings":["Ryerson Univeristy,Department of Electrical and Computer Engineering,Toronto,ON,Canada,M5B2K3"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ryerson Univeristy,Department of Electrical and Computer Engineering,Toronto,ON,Canada,M5B2K3","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7262,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.92211989,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"2022","issue":null,"first_page":"1548","last_page":"1551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9983000159263611,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9980000257492065,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6256641745567322},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6222625374794006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6114250421524048},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5687199234962463},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.563279390335083},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5379989147186279},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4633766710758209},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4567583203315735},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.44618573784828186},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4399353265762329},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43746861815452576},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4232948422431946},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41442108154296875},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3490651845932007},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2767229974269867},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21271249651908875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11946097016334534}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6256641745567322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6222625374794006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6114250421524048},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5687199234962463},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.563279390335083},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5379989147186279},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4633766710758209},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4567583203315735},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.44618573784828186},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4399353265762329},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43746861815452576},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4232948422431946},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41442108154296875},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3490651845932007},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2767229974269867},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21271249651908875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11946097016334534},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":[{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001288","descriptor_name":"Attention","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc48229.2022.9870993","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9870993","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","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 44th Annual International Conference of the IEEE Engineering in Medicine &amp; Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:36086586","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36086586","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2056370875","https://openalex.org/W2748739903","https://openalex.org/W3034797671","https://openalex.org/W3049688872","https://openalex.org/W3091634254","https://openalex.org/W3096831136","https://openalex.org/W3100000627","https://openalex.org/W3168573932","https://openalex.org/W3169967744","https://openalex.org/W4200403734","https://openalex.org/W4200593308"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W1549363203","https://openalex.org/W2147697413","https://openalex.org/W2154063878","https://openalex.org/W4231274751","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W2571255492"],"abstract_inverted_index":{"With":[0],"the":[1,5,24,61,73,79,107,114,136,148,154,158],"increasing":[2],"concern":[3],"regarding":[4,78],"radiation":[6],"exposure":[7],"of":[8,26,81,113,153],"patients":[9],"undergoing":[10],"computed":[11],"tomography":[12],"(CT)":[13],"scans,":[14],"researchers":[15],"have":[16],"been":[17],"using":[18],"deep":[19],"learning":[20],"techniques":[21],"to":[22,123],"improve":[23],"quality":[25],"denoised":[27,62,109,137],"low-dose":[28],"CT":[29,63],"(LDCT)":[30],"images.":[31,138],"In":[32],"this":[33],"paper,":[34],"a":[35,67,111,140],"cascaded":[36],"dilated":[37,169],"residual":[38],"network":[39],"(ResNet)":[40],"with":[41,70,157,171],"integrated":[42],"attention":[43,49,58],"modules,":[44,50],"specifically":[45],"spatial-":[46],"and":[47,71,88,130,150,168],"channel-":[48],"is":[51,93,118],"proposed.":[52],"This":[53],"experiment":[54],"demonstrated":[55],"how":[56,102],"these":[57,103,115],"modules":[59],"improved":[60],"image":[64],"by":[65,146],"testing":[66,142],"simple":[68],"ResNet":[69],"without":[72],"modules.":[74],"Further,":[75],"an":[76,97],"investigation":[77],"effectiveness":[80],"per-pixel":[82],"loss,":[83],"perceptual":[84],"loss":[85,91,104,116],"via":[86],"VGG16-Net,":[87],"structural":[89,133],"dissimilarity":[90],"functions":[92,105],"also":[94,144],"covered":[95],"through":[96],"ablation":[98],"experiment.":[99],"By":[100],"knowing":[101],"affect":[106],"output":[108],"images,":[110],"combination":[112],"function":[117],"then":[119],"proposed":[120,155],"which":[121],"aims":[122],"prevent":[124],"edge":[125,172],"over-smoothing,":[126],"enhance":[127],"textural":[128],"details":[129,134],"finally,":[131],"preserve":[132],"on":[135],"Finally,":[139],"bench":[141],"was":[143],"done":[145],"comparing":[147],"visual":[149],"quantitative":[151],"results":[152],"model":[156],"state-of-the-art":[159],"models":[160],"such":[161],"as":[162],"block":[163],"matching":[164],"3D":[165],"(BM3D),":[166],"patch-GAN":[167],"convolution":[170],"detection":[173],"layer":[174],"(DRL-E-MP)":[175],"for":[176],"accuracy.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
