{"id":"https://openalex.org/W4387459366","doi":"https://doi.org/10.1186/s12880-023-01108-0","title":"DMF-Net: a deep multi-level semantic fusion network for high-resolution chest CT and X-ray image de-noising","display_name":"DMF-Net: a deep multi-level semantic fusion network for high-resolution chest CT and X-ray image de-noising","publication_year":2023,"publication_date":"2023-10-09","ids":{"openalex":"https://openalex.org/W4387459366","doi":"https://doi.org/10.1186/s12880-023-01108-0","pmid":"https://pubmed.ncbi.nlm.nih.gov/37814250"},"language":"en","primary_location":{"id":"doi:10.1186/s12880-023-01108-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-023-01108-0","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-023-01108-0","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-023-01108-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103106757","display_name":"Tapan K. Nayak","orcid":"https://orcid.org/0000-0003-4555-937X"},"institutions":[{"id":"https://openalex.org/I189109744","display_name":"Indian Institute of Technology Dhanbad","ror":"https://ror.org/013v3cc28","country_code":"IN","type":"education","lineage":["https://openalex.org/I189109744"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tapan Kumar Nayak","raw_affiliation_strings":["Department of CSE, IIT(ISM) Dhanbad, Sardar Patel Nagar, Dhanbad, 826004, Jharkhand, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, IIT(ISM) Dhanbad, Sardar Patel Nagar, Dhanbad, 826004, Jharkhand, India","institution_ids":["https://openalex.org/I189109744"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093029210","display_name":"Chandra Sekhara Rao Annavarappu","orcid":null},"institutions":[{"id":"https://openalex.org/I189109744","display_name":"Indian Institute of Technology Dhanbad","ror":"https://ror.org/013v3cc28","country_code":"IN","type":"education","lineage":["https://openalex.org/I189109744"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandra Sekhara Rao Annavarappu","raw_affiliation_strings":["Department of CSE, IIT(ISM) Dhanbad, Sardar Patel Nagar, Dhanbad, 826004, Jharkhand, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, IIT(ISM) Dhanbad, Sardar Patel Nagar, Dhanbad, 826004, Jharkhand, India","institution_ids":["https://openalex.org/I189109744"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090967969","display_name":"Soumya Ranjan Nayak","orcid":"https://orcid.org/0000-0002-4155-884X"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Soumya Ranjan Nayak","raw_affiliation_strings":["School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092060461","display_name":"Berihun Molla Gedefaw","orcid":"https://orcid.org/0000-0002-8602-8770"},"institutions":[{"id":"https://openalex.org/I42869670","display_name":"Arba Minch University","ror":"https://ror.org/00ssp9h11","country_code":"ET","type":"education","lineage":["https://openalex.org/I42869670"]}],"countries":["ET"],"is_corresponding":true,"raw_author_name":"Berihun Molla Gedefaw","raw_affiliation_strings":["Department of Health Informatics, Arba Minch University College of Medicine and Health Science, Arba Minch, Ethiopia. berihunmolla44@gmail.com","Department of Health Informatics, Arba Minch University College of Medicine and Health Science, Arba Minch, Ethiopia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Health Informatics, Arba Minch University College of Medicine and Health Science, Arba Minch, Ethiopia. berihunmolla44@gmail.com","institution_ids":["https://openalex.org/I42869670"]},{"raw_affiliation_string":"Department of Health Informatics, Arba Minch University College of Medicine and Health Science, Arba Minch, Ethiopia","institution_ids":["https://openalex.org/I42869670"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092060461"],"corresponding_institution_ids":["https://openalex.org/I42869670"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":0.9762,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.74214984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"23","issue":"1","first_page":"150","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9990000128746033,"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":0.9990000128746033,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9968000054359436,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9916999936103821,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7862393856048584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.725967288017273},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7242139577865601},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.692253053188324},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6449474096298218},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6176932454109192},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5168890953063965},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5107498168945312},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49357306957244873},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4516066014766693},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.4152683913707733},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37939006090164185},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09601056575775146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7862393856048584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.725967288017273},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7242139577865601},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.692253053188324},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6449474096298218},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6176932454109192},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5168890953063965},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5107498168945312},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49357306957244873},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4516066014766693},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.4152683913707733},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37939006090164185},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09601056575775146},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":"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":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012660","descriptor_name":"Semantics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014965","descriptor_name":"X-Rays","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12880-023-01108-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-023-01108-0","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-023-01108-0","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},{"id":"pmid:37814250","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37814250","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":"BMC medical imaging","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10561479","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10561479","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10561479/pdf/12880_2023_Article_1108.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Imaging","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:2dc15736be304c8e810acc56a4284aa6","is_oa":true,"landing_page_url":"https://doaj.org/article/2dc15736be304c8e810acc56a4284aa6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Imaging, Vol 23, Iss 1, Pp 1-15 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s12880-023-01108-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-023-01108-0","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-023-01108-0","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387459366.pdf"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W305685286","https://openalex.org/W1665214252","https://openalex.org/W1852344107","https://openalex.org/W2007052121","https://openalex.org/W2028611962","https://openalex.org/W2034444692","https://openalex.org/W2034614031","https://openalex.org/W2048695508","https://openalex.org/W2056370875","https://openalex.org/W2069368662","https://openalex.org/W2082910045","https://openalex.org/W2091531059","https://openalex.org/W2107173455","https://openalex.org/W2113945798","https://openalex.org/W2136396015","https://openalex.org/W2148514738","https://openalex.org/W2173423263","https://openalex.org/W2194775991","https://openalex.org/W2207282238","https://openalex.org/W2292560765","https://openalex.org/W2326837237","https://openalex.org/W2510850936","https://openalex.org/W2542870090","https://openalex.org/W2546302380","https://openalex.org/W2584483805","https://openalex.org/W2788633781","https://openalex.org/W2790477006","https://openalex.org/W2894629025","https://openalex.org/W2912435603","https://openalex.org/W2914645392","https://openalex.org/W2914890787","https://openalex.org/W2930362209","https://openalex.org/W2942824232","https://openalex.org/W2964101377","https://openalex.org/W2964342346","https://openalex.org/W3104324122","https://openalex.org/W3191134273","https://openalex.org/W6600708310","https://openalex.org/W6601013545","https://openalex.org/W6602254124","https://openalex.org/W7015098694"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4313906399","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Medical":[0],"images":[1,23,55,82,226],"such":[2,47],"as":[3],"CT":[4,79,144,223],"and":[5,18,31,56,80,145,165,217,224,229,255],"X-ray":[6,81,146,225],"have":[7,92],"been":[8],"widely":[9],"used":[10],"for":[11,137],"the":[12,51,54,59,63,75,105,108,118,138,181,200,206,211,237,240,248,265],"detection":[13],"of":[14,29,46,53,65,117,140,152,239,250],"several":[15],"chest":[16,78,143],"infections":[17],"lung":[19],"diseases.":[20],"However,":[21,99],"these":[22,37],"are":[24,189,232],"susceptible":[25],"to":[26,35,40,73,84,192,194,243],"different":[27,184],"types":[28],"noise,":[30],"it":[32],"is":[33,70,133],"hard":[34],"remove":[36,74],"noises":[38],"due":[39],"their":[41],"complex":[42],"distribution.":[43],"The":[44,148,178],"presence":[45],"noise":[48,76,106,141,167,197,231],"significantly":[49,57],"deteriorates":[50],"quality":[52],"affects":[58],"diagnosis":[60],"performance.":[61],"Hence,":[62],"design":[64],"an":[66],"effective":[67],"de-noising":[68,97,213],"technique":[69],"highly":[71],"essential":[72],"from":[77,107,142,183],"prior":[83],"further":[85],"processing.":[86],"Deep":[87],"learning":[88,162],"methods,":[89],"mainly,":[90],"CNN":[91,101],"shown":[93],"tremendous":[94],"progress":[95],"on":[96,264],"tasks.":[98],"existing":[100],"based":[102],"models":[103],"estimate":[104],"final":[109],"layers,":[110],"which":[111,188],"may":[112],"not":[113],"carry":[114],"adequate":[115],"details":[116],"image.":[119,208],"To":[120,209],"tackle":[121],"this":[122,125],"issue,":[123],"in":[124,247],"paper":[126],"a":[127,153,159,166,173,215,218],"deep":[128],"multi-level":[129],"semantic":[130],"fusion":[131,168],"network":[132],"proposed,":[134],"called":[135],"DMF-Net":[136,149,241],"removal":[139],"images.":[147],"mainly":[150],"comprises":[151],"dilated":[154],"convolutional":[155],"feature":[156,161,175],"extraction":[157,176],"block,":[158],"cascaded":[160],"block":[163,169],"(CFLB)":[164],"(NFB)":[170],"followed":[171],"by":[172],"prominent":[174],"block.":[177],"CFLB":[179],"cascades":[180],"features":[182],"levels":[185],"(convolutional":[186],"layers)":[187],"later":[190],"fed":[191],"NFB":[193],"attain":[195],"correct":[196],"prediction.":[198],"Finally,":[199],"Prominent":[201],"Feature":[202],"Extraction":[203],"Block(PFEB)":[204],"produces":[205],"clean":[207],"validate":[210],"proposed":[212],"technique,":[214],"separate":[216],"mixed":[219],"dataset":[220],"containing":[221],"high-resolution":[222],"with":[227],"specific":[228],"blind":[230],"used.":[233],"Experimental":[234],"results":[235],"indicate":[236],"effectiveness":[238],"compared":[242],"other":[244],"state-of-the-art":[245],"methods":[246],"context":[249],"peak":[251],"signal-to-noise":[252],"ratio":[253],"(PSNR)":[254],"structural":[256],"similarity":[257],"measurement":[258],"(SSIM)":[259],"while":[260],"drastically":[261],"cutting":[262],"down":[263],"processing":[266],"power":[267],"needed.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}