{"id":"https://openalex.org/W4415748203","doi":"https://doi.org/10.1109/tmi.2025.3627516","title":"Deep Residual Compensation Model for Unsupervised PET Partial Volume Correction","display_name":"Deep Residual Compensation Model for Unsupervised PET Partial Volume Correction","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415748203","doi":"https://doi.org/10.1109/tmi.2025.3627516","pmid":"https://pubmed.ncbi.nlm.nih.gov/41171683"},"language":"en","primary_location":{"id":"doi:10.1109/tmi.2025.3627516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3627516","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},"type":"article","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/A5101921367","display_name":"Jianan Cui","orcid":"https://orcid.org/0000-0003-4923-7685"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianan Cui","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4923-7685","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiankai Wu","orcid":"https://orcid.org/0009-0001-1274-829X"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiankai Wu","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-1274-829X","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhongxue Wu","orcid":"https://orcid.org/0009-0003-1246-9076"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongxue Wu","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-1246-9076","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024067111","display_name":"Jianzhong He","orcid":"https://orcid.org/0000-0003-1256-472X"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianzhong He","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021979237","display_name":"Qingrun Zeng","orcid":"https://orcid.org/0000-0001-6485-8178"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingrun Zeng","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6485-8178","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101500691","display_name":"Zan Chen","orcid":"https://orcid.org/0000-0003-4252-4761"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zan Chen","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4252-4761","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100629982","display_name":"Yuanjing Feng","orcid":"https://orcid.org/0000-0002-9398-5456"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjing Feng","raw_affiliation_strings":["College of Information Engineering, Zhejiang University of Technology, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9398-5456","affiliations":[{"raw_affiliation_string":"College of Information Engineering, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":0.8661,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78934795,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"45","issue":"4","first_page":"1432","last_page":"1445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9950000047683716,"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":0.9950000047683716,"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/T11216","display_name":"Radiation Detection and Scintillator Technologies","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.00039999998989515007,"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/partial-volume","display_name":"Partial volume","score":0.7922000288963318},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7013000249862671},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.6288999915122986},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6183000206947327},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6097999811172485},{"id":"https://openalex.org/keywords/imaging-phantom","display_name":"Imaging phantom","score":0.60589998960495},{"id":"https://openalex.org/keywords/positron-emission-tomography","display_name":"Positron emission tomography","score":0.5770000219345093},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5094000101089478},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.49970000982284546},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4674000144004822}],"concepts":[{"id":"https://openalex.org/C82233179","wikidata":"https://www.wikidata.org/wiki/Q2054500","display_name":"Partial volume","level":2,"score":0.7922000288963318},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7013000249862671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6898999810218811},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.6288999915122986},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6183000206947327},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6097999811172485},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.60589998960495},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.5770000219345093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5511000156402588},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5094000101089478},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.49970000982284546},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C199374082","wikidata":"https://www.wikidata.org/wiki/Q907080","display_name":"Standardized uptake value","level":3,"score":0.4221000075340271},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3882000148296356},{"id":"https://openalex.org/C3017724952","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Pet imaging","level":3,"score":0.3792000114917755},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.36419999599456787},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35679998993873596},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C2989005","wikidata":"https://www.wikidata.org/wiki/Q214963","display_name":"Nuclear medicine","level":1,"score":0.3490999937057495},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3336000144481659},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.32089999318122864},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3176000118255615},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.30959999561309814},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2928999960422516},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29179999232292175},{"id":"https://openalex.org/C127077266","wikidata":"https://www.wikidata.org/wiki/Q3488638","display_name":"PET-CT","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.26339998841285706}],"mesh":[{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069558","descriptor_name":"Unsupervised Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","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":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D049268","descriptor_name":"Positron-Emission Tomography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tmi.2025.3627516","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmi.2025.3627516","pdf_url":null,"source":{"id":"https://openalex.org/S58069681","display_name":"IEEE Transactions on Medical Imaging","issn_l":"0278-0062","issn":["0278-0062","1558-254X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Medical Imaging","raw_type":"journal-article"},{"id":"pmid:41171683","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41171683","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":"IEEE transactions on medical imaging","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2819859297","display_name":null,"funder_award_id":"2021R52004","funder_id":"https://openalex.org/F4320338110","funder_display_name":"Science and Technology Department of Zhejiang Province"},{"id":"https://openalex.org/G3389635133","display_name":null,"funder_award_id":"62303413","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3733670675","display_name":null,"funder_award_id":"U23A20334","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4365591683","display_name":null,"funder_award_id":"2024C03093","funder_id":"https://openalex.org/F4320338110","funder_display_name":"Science and Technology Department of Zhejiang Province"},{"id":"https://openalex.org/G588553394","display_name":null,"funder_award_id":"62572440","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6927565164","display_name":null,"funder_award_id":"62101488","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7182076136","display_name":"\u57fa\u4e8e\u4e2a\u4f53\u5316\u9885\u795e\u7ecf\u81ea\u52a8\u8bc6\u522b\u7684\u9885\u5e95\u624b\u672f\u89c4\u5212\u65b9\u6cd5\u7814\u7a76","funder_award_id":"LQ23F030017","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G7464499840","display_name":null,"funder_award_id":"62403428","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338110","display_name":"Science and Technology Department of Zhejiang Province","ror":"https://ror.org/05yj3y977"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Partial":[0],"volume":[1,42],"effect":[2],"(PVE)":[3],"arises":[4],"from":[5],"the":[6,53,79,101,105,110,153,187,220],"limited":[7],"spatial":[8],"resolution":[9],"of":[10,115,210,222],"positron":[11],"emission":[12],"tomography":[13],"(PET)":[14],"scanners,":[15],"causing":[16],"significant":[17],"quantitative":[18,163],"biases":[19],"that":[20,216],"hinder":[21],"accurate":[22],"metabolic":[23],"activity":[24],"assessment.":[25],"To":[26],"address":[27],"these":[28],"problems,":[29],"we":[30],"proposed":[31],"an":[32,48,172],"unsupervised":[33,91],"deep":[34,138],"residual":[35,69],"compensation":[36,70],"model":[37,89],"(U-DRCM)":[38],"for":[39,52,78],"PET":[40,55,98,228],"partial":[41],"correction":[43],"(PVC).":[44],"U-DRCM":[45,116,156,191,217],"first":[46],"predicted":[47],"initial":[49],"blur":[50,84],"kernel":[51,85],"PVE-affected":[54],"image":[56,99,108],"based":[57],"on":[58],"a":[59,67,95,166,179],"conditional":[60,68],"blind":[61,134],"deconvolution":[62,135],"module":[63,71],"(CBD":[64],"module).":[65],"Then,":[66],"(CRC":[72],"module)":[73],"was":[74,117],"introduced":[75],"to":[76],"compensate":[77],"error":[80,184],"caused":[81],"by":[82],"inaccurate":[83],"prediction.":[86],"The":[87,113],"whole":[88],"is":[90],"which":[92],"only":[93],"needs":[94],"single":[96],"patient's":[97],"as":[100,109],"training":[102],"label":[103],"and":[104,137,148,178,200],"corresponding":[106],"MR":[107],"network":[111,141],"input.":[112],"performance":[114],"evaluated":[118],"against":[119],"several":[120],"established":[121],"PVC":[122,227],"approaches,":[123],"including":[124],"Richardson-Lucy":[125],"(RL),":[126],"reblurred":[127],"Van-Cittert":[128],"(RVC),":[129],"iterative":[130],"Yang":[131],"(IY),":[132],"neural":[133,140],"(NBD),":[136],"convolutional":[139],"(DeepPVC)":[142],"using":[143],"both":[144],"simulated":[145],"BrainWeb":[146],"phantom":[147],"real":[149,188],"clinical":[150,189],"datasets.":[151],"In":[152],"simulation":[154],"study,":[155,190],"consistently":[157],"outperformed":[158],"competing":[159],"methods":[160],"across":[161,206],"multiple":[162],"metrics,":[164],"achieved":[165],"higher":[167],"peak":[168],"signal-to-noise":[169],"ratio":[170,204],"(PSNR),":[171],"improved":[173],"structural":[174],"similarity":[175],"index":[176],"(SSIM),":[177],"lower":[180],"root":[181],"mean":[182],"square":[183],"(RMSE).":[185],"For":[186],"delivered":[192],"substantial":[193],"improvements":[194],"in":[195,225],"standardized":[196,201],"uptake":[197,202],"value":[198,203],"(SUV)":[199],"(SUVR)":[205],"various":[207],"brain":[208,232],"volumes":[209],"interest":[211],"(VOIs).":[212],"Experimental":[213],"results":[214],"show":[215],"effectively":[218],"mitigates":[219],"impact":[221],"PVE,":[223],"resulting":[224],"high-quality":[226],"images":[229],"with":[230],"enhanced":[231],"visualization.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-13T07:31:44.756512","created_date":"2025-10-31T00:00:00"}