{"id":"https://openalex.org/W7126031719","doi":"https://doi.org/10.1109/bibm66473.2025.11356644","title":"Self-Supervised Low-Dose CT Denoising via Global Patch Matching and Diffusion Refinement","display_name":"Self-Supervised Low-Dose CT Denoising via Global Patch Matching and Diffusion Refinement","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126031719","doi":"https://doi.org/10.1109/bibm66473.2025.11356644"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5002153254","display_name":"Boheng Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boheng Tan","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chen","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124241112","display_name":"Xuan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xuan Liu","raw_affiliation_strings":["The Hong Kong Polytechnic University,Department of Health Technology and Informatics,Hong Kong SAR,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University,Department of Health Technology and Informatics,Hong Kong SAR,China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124254926","display_name":"Shan Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Tan","raw_affiliation_strings":["School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5712","last_page":"5717"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.6158000230789185,"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"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.6158000230789185,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.1412999927997589,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.04050000011920929,"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/noise-reduction","display_name":"Noise reduction","score":0.8102999925613403},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5878000259399414},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5529999732971191},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.507099986076355},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.507099986076355},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4973999857902527},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4627000093460083},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.43869999051094055}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.8102999925613403},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7139999866485596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.59170001745224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5529999732971191},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5199999809265137},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.507099986076355},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.507099986076355},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4973999857902527},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4627000093460083},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.43869999051094055},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.40130001306533813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.3720000088214874},{"id":"https://openalex.org/C203504353","wikidata":"https://www.wikidata.org/wiki/Q4765461","display_name":"Anisotropic diffusion","level":3,"score":0.3659000098705292},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.29429998993873596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29109999537467957},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27239999175071716},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.258899986743927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3043370997","display_name":null,"funder_award_id":"62071197,62471192","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2122546849","https://openalex.org/W2160850888","https://openalex.org/W2762996341","https://openalex.org/W2902857081","https://openalex.org/W2952020389","https://openalex.org/W2962793481","https://openalex.org/W2997316188","https://openalex.org/W3047011367","https://openalex.org/W3098281398","https://openalex.org/W3155072588","https://openalex.org/W3178192988","https://openalex.org/W4312730028","https://openalex.org/W4312773500","https://openalex.org/W4386076517","https://openalex.org/W4405488258","https://openalex.org/W4408125743"],"related_works":[],"abstract_inverted_index":{"Supervised":[0],"deep":[1],"denoising":[2,11,39,69,186],"methods":[3,27,49],"have":[4],"significantly":[5],"advanced":[6],"low-dose":[7,37,44,158,191],"computed":[8],"tomography":[9],"(CT)":[10],"but":[12],"require":[13],"paired":[14],"clean-noisy":[15],"samples":[16],"that":[17,85,174],"are":[18,28,50,135],"often":[19],"unavailable":[20],"in":[21],"clinical":[22],"applications.":[23],"Current":[24],"most":[25],"self-supervised":[26,92,179],"motivated":[29],"by":[30,52,95],"the":[31,96,126,131,149],"Noise2Noise":[32],"framework":[33],"and":[34,116],"achieve":[35],"successful":[36],"CT":[38,45,111,133,144,159,192],"based":[40],"on":[41,141],"massive":[42],"adjacent":[43],"slices.":[46,193],"However,":[47],"these":[48],"limited":[51],"slice-similarity":[53],"necessity":[54],"with":[55,62,167,188],"small":[56],"slice":[57,60],"spacing.":[58],"Large":[59],"spacing":[61],"spatial":[63],"misalignment":[64],"brings":[65],"inaccurate":[66],"predictions":[67],"of":[68],"results,":[70],"necessitating":[71],"more":[72],"general":[73],"method.":[74,180],"To":[75],"this":[76],"end,":[77],"we":[78],"propose":[79],"Global":[80],"Patch":[81],"Matching-Diffusion":[82],"Refinement":[83],"method":[84,176],"constructs":[86],"global":[87,107],"volume":[88],"similar":[89,108],"images":[90,134,145],"for":[91],"optimization,":[93],"followed":[94],"perceptual":[97,150],"refinement":[98],"from":[99,110],"diffusion":[100,138],"models,":[101],"termed":[102],"GPM-DR.":[103],"Our":[104],"approach":[105],"extracts":[106],"patches":[109],"sequences":[112],"via":[113],"mask":[114],"similarity":[115],"<tex":[117],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathrm{L}^{2}$</tex>":[119],"norm-based":[120],"sliding":[121],"window":[122],"matching,":[123],"which":[124],"enriches":[125],"training":[127],"data":[128],"diversity.":[129],"Subsequently,":[130],"denoised":[132],"incorporated":[136],"into":[137],"models":[139],"conditioned":[140],"constructed":[142],"noisy":[143],"to":[146],"further":[147],"refine":[148],"image":[151,160],"quality.":[152],"The":[153,171],"proposed":[154],"GPM-DR":[155],"effectively":[156],"mitigates":[157],"noise":[161],"while":[162],"addressing":[163],"discrepancies":[164],"between":[165],"slices":[166],"powerful":[168],"generative":[169],"ability.":[170],"results":[172],"demonstrate":[173,183],"our":[175],"outperforms":[177],"representative":[178],"Extensive":[181],"experiments":[182],"its":[184],"exceptional":[185],"performance":[187],"few":[189],"original":[190]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}
