{"id":"https://openalex.org/W7148269240","doi":"https://doi.org/10.1186/s12859-026-06429-9","title":"Adaptive enhancement of chest X-ray images using tissue attenuation and local and global fusion","display_name":"Adaptive enhancement of chest X-ray images using tissue attenuation and local and global fusion","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148269240","doi":"https://doi.org/10.1186/s12859-026-06429-9","pmid":"https://pubmed.ncbi.nlm.nih.gov/41928064"},"language":"en","primary_location":{"id":"doi:10.1186/s12859-026-06429-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06429-9","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s12859-026-06429-9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132787752","display_name":"Zhen Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116886","display_name":"Chongqing Vocational Institute of Engineering","ror":"https://ror.org/0279ehd23","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116886"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Zhao","raw_affiliation_strings":["Big Data and Internet of Things School, Chongqing Vocational Institute of Engineering, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Big Data and Internet of Things School, Chongqing Vocational Institute of Engineering, Chongqing, China","institution_ids":["https://openalex.org/I4210116886"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101688423","display_name":"Rui Tang","orcid":"https://orcid.org/0000-0002-4466-316X"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Rui Tang","raw_affiliation_strings":["Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist University, Zhuhai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Science and Technology, Beijing Normal-Hong Kong Baptist University, Zhuhai, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101816327","display_name":"Qifeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Qifeng Liu","raw_affiliation_strings":["School of Computer Science, University of Birmingham, Birmingham, UK. qxl568@student.bham.ac.uk"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Birmingham, Birmingham, UK. qxl568@student.bham.ac.uk","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101816327"],"corresponding_institution_ids":["https://openalex.org/I79619799"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27915998,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.4912000000476837,"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/T11019","display_name":"Image Enhancement Techniques","score":0.4912000000476837,"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/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.13619999587535858,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.08259999752044678,"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/visibility","display_name":"Visibility","score":0.7943999767303467},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5849000215530396},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.5548999905586243},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.5496000051498413},{"id":"https://openalex.org/keywords/contrast-enhancement","display_name":"Contrast enhancement","score":0.5475999712944031},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5428000092506409},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.534500002861023},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48410001397132874},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4108000099658966}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.7943999767303467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7330999970436096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7311000227928162},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6294000148773193},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5849000215530396},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.5548999905586243},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.5496000051498413},{"id":"https://openalex.org/C3018181011","wikidata":"https://www.wikidata.org/wiki/Q6849688","display_name":"Contrast enhancement","level":3,"score":0.5475999712944031},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5428000092506409},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.534500002861023},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48410001397132874},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3952000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.37119999527931213},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C3018302497","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Image contrast","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2590000033378601},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.25}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","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":"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":"D011856","descriptor_name":"Radiographic Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011856","descriptor_name":"Radiographic Image Enhancement","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.1186/s12859-026-06429-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06429-9","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},{"id":"pmid:41928064","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41928064","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 bioinformatics","raw_type":"Journal Article"},{"id":"pmh:oai:pure.atira.dk:openaire/7574fd1e-4c40-4298-b6fe-d99be3e0ff46","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/7574fd1e-4c40-4298-b6fe-d99be3e0ff46","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Zhao, Z, Tang, R & Liu, Q 2026, 'Adaptive enhancement of chest X-ray images using tissue attenuation and local and global fusion', BMC Bioinformatics, vol. 27, no. 1, 101. https://doi.org/10.1186/s12859-026-06429-9","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:d44bac467b9c4d168c72bd3adbf95f2a","is_oa":true,"landing_page_url":"https://doaj.org/article/d44bac467b9c4d168c72bd3adbf95f2a","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 Bioinformatics, Vol 27, Iss 1 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13170285","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13170285/","pdf_url":null,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Bioinformatics","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12859-026-06429-9","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12859-026-06429-9","pdf_url":null,"source":{"id":"https://openalex.org/S19032547","display_name":"BMC Bioinformatics","issn_l":"1471-2105","issn":["1471-2105"],"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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Bioinformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1552073401","https://openalex.org/W1977725648","https://openalex.org/W2016622085","https://openalex.org/W2045779008","https://openalex.org/W2137619600","https://openalex.org/W2142514727","https://openalex.org/W2587580983","https://openalex.org/W2594112328","https://openalex.org/W2750924099","https://openalex.org/W2946105014","https://openalex.org/W2979411237","https://openalex.org/W2995213326","https://openalex.org/W3026610549","https://openalex.org/W3109680477","https://openalex.org/W3110242322","https://openalex.org/W3135057764","https://openalex.org/W3174416962","https://openalex.org/W3178773782","https://openalex.org/W3183670897","https://openalex.org/W4206313534","https://openalex.org/W4214877435","https://openalex.org/W4220950354","https://openalex.org/W4322770975","https://openalex.org/W4361792510","https://openalex.org/W4387211699","https://openalex.org/W4390839392","https://openalex.org/W4390950050","https://openalex.org/W4400232627","https://openalex.org/W4408165995","https://openalex.org/W4408958047","https://openalex.org/W4410253038"],"related_works":[],"abstract_inverted_index":{"Chest":[0],"X-ray":[1,82],"images":[2],"often":[3],"suffer":[4],"from":[5],"low":[6],"contrast,":[7,159],"noise,":[8],"and":[9,22,25,30,45,95,106,120,146,161,174],"loss":[10],"of":[11,20,118,124,163],"local":[12,104],"details,":[13,105],"which":[14],"can":[15],"hinder":[16],"the":[17,122,155],"accurate":[18],"identification":[19],"bones":[21,119],"soft":[23],"tissues":[24],"affect":[26],"subsequent":[27],"automated":[28],"diagnosis":[29],"clinical":[31],"interpretation.":[32],"To":[33],"address":[34],"these":[35],"challenges,":[36],"recent":[37],"methods":[38,52],"have":[39],"explored":[40],"both":[41],"traditional":[42,173],"contrast":[43,61,93],"enhancement":[44,78,177],"deep":[46,175],"learning-based":[47,176],"strategies.":[48],"However,":[49],"most":[50],"existing":[51,172],"focus":[53],"on":[54,150],"a":[55,96],"single":[56],"degradation":[57],"factor,":[58],"such":[59],"as":[60],"enhancement,":[62,90],"without":[63],"explicitly":[64],"considering":[65],"region-specific":[66],"visibility":[67,89,117,162],"or":[68],"structure-aware":[69],"enhancement.":[70],"In":[71],"this":[72],"work,":[73],"we":[74],"propose":[75],"an":[76],"adaptive":[77],"approach":[79,140],"for":[80],"chest":[81],"images.":[83],"Our":[84],"framework":[85],"integrates":[86],"tissue":[87],"attenuation":[88],"linear":[91],"transformation-based":[92],"adjustment,":[94],"perceptual":[97],"fusion":[98],"module":[99],"to":[100,112],"emphasize":[101],"anatomical":[102,126,164],"features,":[103],"global":[107],"brightness.":[108],"This":[109],"design":[110],"aims":[111],"suppress":[113],"soft-tissue":[114],"interference,":[115],"improve":[116,121],"visualization":[123],"essential":[125],"components,":[127],"while":[128],"maintaining":[129],"consistent":[130],"image":[131,158],"quality":[132],"across":[133],"regions":[134],"with":[135,170],"varying":[136],"exposure.":[137],"Importantly,":[138],"our":[139],"does":[141],"not":[142],"require":[143],"extensive":[144],"training":[145],"is":[147],"interpretable.":[148],"Experiments":[149],"benchmark":[151],"datasets":[152],"demonstrate":[153],"that":[154],"method":[156],"improves":[157],"sharpness,":[160],"structures,":[165],"showing":[166],"promising":[167],"results":[168],"compared":[169],"12":[171],"methods.":[178]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-04-03T00:00:00"}
