{"id":"https://openalex.org/W7204181559","doi":"https://doi.org/10.1088/2057-1976/ae9e36","title":"Impact of noise power spectrum (NPS) peak frequency on CT radiomics features: a computational phantom study","display_name":"Impact of noise power spectrum (NPS) peak frequency on CT radiomics features: a computational phantom study","publication_year":2026,"publication_date":"2026-08-25","ids":{"openalex":"https://openalex.org/W7204181559","doi":"https://doi.org/10.1088/2057-1976/ae9e36","pmid":"https://pubmed.ncbi.nlm.nih.gov/42641623"},"language":"en","primary_location":{"id":"doi:10.1088/2057-1976/ae9e36","doi":"https://doi.org/10.1088/2057-1976/ae9e36","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2057-1976/ae9e36","pdf_url":"https://iopscience.iop.org/article/10.1088/2057-1976/ae9e36/pdf","source":{"id":"https://openalex.org/S2764445381","display_name":"Biomedical Physics & Engineering Express","issn_l":"2057-1976","issn":["2057-1976"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","ki-jl-1","medline","norway-1"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"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":"Biomedical Physics &amp; Engineering Express","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://iopscience.iop.org/article/10.1088/2057-1976/ae9e36/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147963819","display_name":"Muhammad Rifqi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I11855966","display_name":"Diponegoro University","ror":"https://ror.org/056bjta22","country_code":"ID","type":"education","lineage":["https://openalex.org/I11855966"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhammad Rifqi","raw_affiliation_strings":["Diponegoro University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Diponegoro University","institution_ids":["https://openalex.org/I11855966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045657396","display_name":"Choirul Anam","orcid":"https://orcid.org/0000-0003-0156-6797","observed_orcids":["https://orcid.org/0000-0003-0156-6797"]},"institutions":[{"id":"https://openalex.org/I11855966","display_name":"Diponegoro University","ror":"https://ror.org/056bjta22","country_code":"ID","type":"education","lineage":["https://openalex.org/I11855966"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Choirul Anam","raw_affiliation_strings":["Diponegoro University"],"raw_orcid":"https://orcid.org/0000-0003-0156-6797","affiliations":[{"raw_affiliation_string":"Diponegoro University","institution_ids":["https://openalex.org/I11855966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003598102","display_name":"Pandji Triadyaksa","orcid":"https://orcid.org/0000-0001-7536-3592","observed_orcids":["https://orcid.org/0000-0001-7536-3592"]},"institutions":[{"id":"https://openalex.org/I11855966","display_name":"Diponegoro University","ror":"https://ror.org/056bjta22","country_code":"ID","type":"education","lineage":["https://openalex.org/I11855966"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Pandji Triadyaksa","raw_affiliation_strings":["Diponegoro University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Diponegoro University","institution_ids":["https://openalex.org/I11855966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065930422","display_name":"Geoff Dougherty","orcid":"https://orcid.org/0000-0003-3187-3595","observed_orcids":["https://orcid.org/0000-0003-3187-3595"]},"institutions":[{"id":"https://openalex.org/I194388944","display_name":"California State University, Channel Islands","ror":"https://ror.org/04v097707","country_code":"US","type":"education","lineage":["https://openalex.org/I194388944"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Geoff Dougherty","raw_affiliation_strings":["Applied Physics and Medical Imaging, California State University Channel Islands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Physics and Medical Imaging, California State University Channel Islands","institution_ids":["https://openalex.org/I194388944"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5045657396"],"corresponding_institution_ids":["https://openalex.org/I11855966"],"apc_list":{"value":2400,"currency":"USD","value_usd":2400},"apc_paid":{"value":2400,"currency":"USD","value_usd":2400},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70180074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"5","first_page":"055004","last_page":"055004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.0,"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":0.0,"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/ct-radiomics","display_name":"CT radiomics","score":0.7950000166893005},{"id":"https://openalex.org/keywords/noise-power-spectrum","display_name":"noise power spectrum","score":0.9589999914169312},{"id":"https://openalex.org/keywords/noise-texture","display_name":"noise texture","score":0.5239999890327454},{"id":"https://openalex.org/keywords/feature-sensitivity","display_name":"feature sensitivity","score":0.38199999928474426},{"id":"https://openalex.org/keywords/gray-level-co-occurrence-matrix","display_name":"gray level co-occurrence matrix","score":0.8700000047683716},{"id":"https://openalex.org/keywords/first-order-features","display_name":"first-order features","score":0.7210000157356262},{"id":"https://openalex.org/keywords/computational-phantoms","display_name":"computational phantoms","score":0.6859999895095825}],"concepts":[{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.6622999906539917},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.6401000022888184},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6259999871253967},{"id":"https://openalex.org/C126674687","wikidata":"https://www.wikidata.org/wiki/Q1662573","display_name":"Akaike information criterion","level":2,"score":0.5694000124931335},{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47360000014305115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46369999647140503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44830000400543213},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3806999921798706},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.3578999936580658},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C96608239","wikidata":"https://www.wikidata.org/wiki/Q1199823","display_name":"Statistical power","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C203234222","wikidata":"https://www.wikidata.org/wiki/Q2133519","display_name":"Noise power","level":3,"score":0.3264999985694885},{"id":"https://openalex.org/C138029060","wikidata":"https://www.wikidata.org/wiki/Q7226633","display_name":"Polynomial and rational function modeling","level":3,"score":0.3172999918460846},{"id":"https://openalex.org/C154020017","wikidata":"https://www.wikidata.org/wiki/Q520171","display_name":"Repeatability","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31290000677108765},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C89838059","wikidata":"https://www.wikidata.org/wiki/Q623738","display_name":"Coefficient of variation","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26759999990463257},{"id":"https://openalex.org/C2778368474","wikidata":"https://www.wikidata.org/wiki/Q5456322","display_name":"Fixed-pattern noise","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.25369998812675476}],"mesh":[{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","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":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","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":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008962","descriptor_name":"Models, Theoretical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D014057","descriptor_name":"Tomography, X-Ray Computed","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019047","descriptor_name":"Phantoms, Imaging","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":2,"locations":[{"id":"doi:10.1088/2057-1976/ae9e36","doi":"https://doi.org/10.1088/2057-1976/ae9e36","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2057-1976/ae9e36","pdf_url":"https://iopscience.iop.org/article/10.1088/2057-1976/ae9e36/pdf","source":{"id":"https://openalex.org/S2764445381","display_name":"Biomedical Physics & Engineering Express","issn_l":"2057-1976","issn":["2057-1976"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","ki-jl-1","medline","norway-1"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"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":"Biomedical Physics &amp; Engineering Express","raw_type":"journal-article"},{"id":"pmid:42641623","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42641623","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,"listed_in":[],"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":"Biomedical physics & engineering express","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1088/2057-1976/ae9e36","doi":"https://doi.org/10.1088/2057-1976/ae9e36","is_oa":true,"landing_page_url":"https://doi.org/10.1088/2057-1976/ae9e36","pdf_url":"https://iopscience.iop.org/article/10.1088/2057-1976/ae9e36/pdf","source":{"id":"https://openalex.org/S2764445381","display_name":"Biomedical Physics & Engineering Express","issn_l":"2057-1976","issn":["2057-1976"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","jufo-1","ki-jl-1","medline","norway-1"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"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":"Biomedical Physics &amp; Engineering Express","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.504800021648407,"display_name":"Good health and well-being"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320328515","display_name":"Lembaga Pengelola Dana Pendidikan","ror":"https://ror.org/05p2xef58"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204181559.pdf","grobid_xml":"https://content.openalex.org/works/W7204181559.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"This":[1,303],"study":[2],"aims":[3],"to":[4,11,21,29,42,67,99,158,162,194,199],"quantify":[5],"the":[6,101,116,138,147,177,182,232,240,300],"sensitivity":[7,134,193],"of":[8,118,140,149,176,210,242],"radiomics":[9,284],"features":[10,133,189,244,257,267,298],"variations":[12],"in":[13,33,186,276,283,299],"noise":[14,50,73,251,264],"power":[15],"spectrum":[16],"(NPS)":[17],"peak":[18,58,62,106,196,278],"frequency":[19,165,234,279],"and":[20,77,86,128,146,217],"develop":[22],"a":[23,163,203,207,306],"robust,":[24],"physics-driven":[25],"non-linear":[26],"correction":[27,154,178,229,254,273,294],"method":[28],"mitigate":[30],"kernel-induced":[31],"variability":[32,282],"extracted":[34],"features.":[35],"A":[36,152],"homogeneous":[37],"computational":[38],"phantom":[39],"was":[40,54,112,135,156,179],"generated":[41],"simulate":[43],"computed":[44],"tomography":[45],"(CT)":[46],"images":[47],"with":[48,56,202],"varying":[49],"textures.":[51],"Noise":[52],"texture":[53],"synthesized":[55],"NPS":[57,277],"frequencies":[59],"(":[60,142,166,212,220],"f":[61,105,167,195],")":[63,145,224],"ranging":[64],"from":[65],"0.3":[66],"1.0":[68],"mm":[69,171],"\u22121":[70,172],"across":[71,249,263],"three":[72],"levels":[74],"(25,":[75],"50,":[76],"75":[78],"HU).":[79],"Radiomics":[80,132],"features,":[81,201,285],"specifically":[82],"first":[83],"order":[84],"(FO)":[85],"gray":[87],"level":[88],"cooccurrence":[89],"matrix":[90],"(GLCM)":[91],"were":[92,97,261],"extracted.":[93],"Four":[94],"mathematical":[95],"models":[96],"evaluated":[98],"characterize":[100],"feature":[102,160],"dependency":[103],"on":[104,115],".":[107,225],"The":[108,174,226,290],"second-order":[109,227,292],"polynomial":[110,228,293],"model":[111],"selected":[113],"based":[114],"optimization":[117],"Akaike":[119],"information":[120],"criterion":[121],"(AIC),":[122],"root":[123],"mean":[124],"square":[125],"error":[126],"(RMSE),":[127],"adjusted":[129],"R":[130,143,213],"-squared.":[131],"assessed":[136],"using":[137,181],"coefficient":[139,148,209],"determination":[141,211],"2":[144,214],"variation":[150],"(COV).":[151],"robust":[153],"algorithm":[155],"developed":[157],"normalize":[159],"values":[161],"reference":[164],"peak,ref":[168],"=":[169],"0.6":[170],").":[173],"efficacy":[175],"quantified":[180],"percentage":[183],"improvement":[184],"(PI)":[185],"COV.":[187],"GLCM":[188,259,269,288],"exhibited":[190],"significantly":[191],"higher":[192],"shifts":[197],"compared":[198],"FO":[200],"large":[204],"proportion":[205],"showing":[206],"high":[208],"\u2248":[215],"1)":[216],"statistical":[218],"significance":[219],"p":[221],"<":[222,246],"0.05":[223],"effectively":[230],"mitigated":[231],"spatial":[233],"dependency.":[235],"Post-correction":[236],"analysis":[237],"demonstrated":[238],"that":[239],"number":[241],"stable":[243],"(COV":[245],"10%)":[247],"increased":[248],"all":[250],"levels.":[252],"Notably,":[253],"parameters":[255],"for":[256,309],"like":[258,268],"Correlation":[260],"consistent":[262],"magnitude,":[265],"whereas":[266],"Contrast":[270],"required":[271],"dose-dependent":[272],"factors.":[274],"Shifts":[275],"introduce":[280],"nonlinear":[281],"disproportionately":[286],"affecting":[287],"metrics.":[289],"proposed":[291],"successfully":[295],"harmonizes":[296],"these":[297],"post-extraction":[301],"domain.":[302],"approach":[304],"offers":[305],"practical":[307],"solution":[308],"standardizing":[310],"retrospective":[311],"multicenter.":[312]},"counts_by_year":[],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2026-08-26T00:00:00"}
