{"id":"https://openalex.org/W4415538014","doi":"https://doi.org/10.1145/3746027.3754934","title":"Lightweight Medical Image Restoration via Integrating Reliable Lesion-Semantic Driven Prior","display_name":"Lightweight Medical Image Restoration via Integrating Reliable Lesion-Semantic Driven Prior","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538014","doi":"https://doi.org/10.1145/3746027.3754934"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3754934","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5058087345","display_name":"Pengcheng Zheng","orcid":"https://orcid.org/0009-0004-3323-9170"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0004-3323-9170","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020579227","display_name":"Kecheng Chen","orcid":"https://orcid.org/0000-0001-6657-3221"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kecheng Chen","raw_affiliation_strings":["City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-6657-3221","affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000576513","display_name":"Jiaxin Huang","orcid":"https://orcid.org/0000-0003-1893-7662"},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Jiaxin Huang","raw_affiliation_strings":["Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"],"raw_orcid":"https://orcid.org/0000-0003-1893-7662","affiliations":[{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bohao Chen","orcid":"https://orcid.org/0009-0002-7153-8185"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bohao Chen","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0002-7153-8185","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103457121","display_name":"Ju Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ju Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0000-5164-9115","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055826974","display_name":"Yazhou Ren","orcid":"https://orcid.org/0000-0001-7705-4603"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210137766","display_name":"Institute for Advanced Study","ror":"https://ror.org/03xg85719","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210137766"]}],"countries":["CN","DE"],"is_corresponding":false,"raw_author_name":"Yazhou Ren","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China and Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7705-4603","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China and Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China","institution_ids":["https://openalex.org/I4210137766","https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103248543","display_name":"Xiaorong Pu","orcid":"https://orcid.org/0000-0001-7387-7194"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210137766","display_name":"Institute for Advanced Study","ror":"https://ror.org/03xg85719","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210137766"]}],"countries":["CN","DE"],"is_corresponding":false,"raw_author_name":"Xiaorong Pu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China and Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7387-7194","affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China and Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China","institution_ids":["https://openalex.org/I4210137766","https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2977","last_page":"2986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.998199999332428,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6805999875068665},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5819000005722046},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.47609999775886536},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.47029998898506165},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4675999879837036},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.46700000762939453},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.43799999356269836},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4050999879837036},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3937000036239624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956999897956848},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6805999875068665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6419000029563904},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5819000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5131999850273132},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.47609999775886536},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.47029998898506165},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4675999879837036},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.46700000762939453},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4050999879837036},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3855000138282776},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.36739999055862427},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36000001430511475},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.33340001106262207},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.29899999499320984},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3754934","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6381694678","display_name":null,"funder_award_id":"No. 6247 6052","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":16,"referenced_works":["https://openalex.org/W2046119925","https://openalex.org/W2127374940","https://openalex.org/W2133665775","https://openalex.org/W2135264048","https://openalex.org/W2157494358","https://openalex.org/W2160331183","https://openalex.org/W2584483805","https://openalex.org/W2589663521","https://openalex.org/W2743780012","https://openalex.org/W3098281398","https://openalex.org/W3125121063","https://openalex.org/W4250518393","https://openalex.org/W4367056946","https://openalex.org/W4381149320","https://openalex.org/W4390650170","https://openalex.org/W4391109864"],"related_works":[],"abstract_inverted_index":{"Medical":[0],"image":[1,23,128],"restoration":[2,39,59],"tasks":[3,196],"aim":[4],"to":[5,116],"recover":[6],"high-quality":[7],"images":[8],"from":[9],"degraded":[10],"observations,":[11],"exhibiting":[12],"emergent":[13],"desires":[14],"in":[15,66,83,93,139,162,194,204],"many":[16],"clinical":[17],"scenarios,":[18],"such":[19],"as":[20],"low-dose":[21],"CT":[22],"denoising,":[24],"MRI":[25,28],"super-resolution,":[26],"and":[27,152,207],"artifact":[29],"removal.":[30],"Despite":[31],"the":[32,55,58,84,90,125,137,140,145,163,166,174,182,198,201],"success":[33],"achieved":[34],"by":[35,89,120,188],"existing":[36],"deep":[37],"learning-based":[38],"methods":[40],"with":[41,46,112],"sophisticated":[42],"modules,":[43],"they":[44,52],"struggle":[45],"rendering":[47],"computationally-efficient":[48],"reconstruction":[49],"results.":[50],"Moreover,":[51],"usually":[53],"ignore":[54],"reliability":[56],"of":[57,134,165,178,185,200],"results,":[60],"which":[61],"is":[62],"much":[63],"more":[64],"urgent":[65],"medical":[67,127],"systems.":[68],"To":[69],"alleviate":[70],"these":[71],"issues,":[72],"we":[73,98,143],"present":[74],"LRformer,":[75],"a":[76,100],"Lightweight":[77],"Transformer-based":[78],"method":[79],"via":[80,156],"Reliability-guided":[81],"learning":[82],"frequency":[85],"domain.":[86],"Specifically,":[87],"inspired":[88],"uncertainty":[91],"quantification":[92],"Bayesian":[94],"neural":[95],"networks":[96],"(BNNs),":[97],"develop":[99],"Reliable":[101],"Lesion-Semantic":[102],"Prior":[103],"Producer":[104],"(RLPP).":[105],"RLPP":[106],"leverages":[107],"Monte":[108],"Carlo":[109],"(MC)":[110],"estimators":[111],"stochastic":[113],"sampling":[114],"operations":[115],"generate":[117],"sufficiently-reliable":[118],"priors":[119,138],"performing":[121],"multiple":[122],"inferences":[123],"on":[124],"foundational":[126],"segmentation":[129],"model,":[130],"MedSAM.":[131],"Additionally,":[132],"instead":[133],"directly":[135],"incorporating":[136],"spatial":[141],"domain,":[142],"decompose":[144],"cross-attention":[146],"(CA)":[147],"mechanism":[148],"into":[149],"real":[150],"symmetric":[151,176],"imaginary":[153],"anti-symmetric":[154],"parts":[155],"fast":[157],"Fourier":[158],"transform":[159],"(FFT),":[160],"resulting":[161],"design":[164],"Guided":[167],"Frequency":[168],"Cross-Attention":[169],"(GFCA)":[170],"solver.":[171],"By":[172],"leveraging":[173],"conjugated":[175],"property":[177],"FFT,":[179],"GFCA":[180],"reduces":[181],"computational":[183],"complexity":[184],"naive":[186],"CA":[187],"nearly":[189],"half.":[190],"Extensive":[191],"experimental":[192],"results":[193],"various":[195],"demonstrate":[197],"superiority":[199],"proposed":[202],"LRformer":[203],"both":[205],"effectiveness":[206],"efficiency.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-25T00:00:00"}