{"id":"https://openalex.org/W4399526722","doi":"https://doi.org/10.1109/access.2024.3412850","title":"A Novel Image Casting and Fusion for Identifying Individuals at Risk of Alzheimer\u2019s Disease Using MRI and PET Imaging","display_name":"A Novel Image Casting and Fusion for Identifying Individuals at Risk of Alzheimer\u2019s Disease Using MRI and PET Imaging","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4399526722","doi":"https://doi.org/10.1109/access.2024.3412850"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3412850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3412850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3412850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048027692","display_name":"A Fakoya","orcid":"https://orcid.org/0000-0001-6686-4811"},"institutions":[{"id":"https://openalex.org/I133837150","display_name":"University of Huddersfield","ror":"https://ror.org/05t1h8f27","country_code":"GB","type":"education","lineage":["https://openalex.org/I133837150"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Adediji A. Fakoya","raw_affiliation_strings":["School of Computing and Engineering, University of Huddersfield, Huddersfield, U.K","School of Computing and Engineering, University of Huddersfield, Huddersfield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Huddersfield, Huddersfield, U.K","institution_ids":["https://openalex.org/I133837150"]},{"raw_affiliation_string":"School of Computing and Engineering, University of Huddersfield, Huddersfield, United Kingdom","institution_ids":["https://openalex.org/I133837150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037686924","display_name":"Simon Parkinson","orcid":"https://orcid.org/0000-0002-1747-9914"},"institutions":[{"id":"https://openalex.org/I133837150","display_name":"University of Huddersfield","ror":"https://ror.org/05t1h8f27","country_code":"GB","type":"education","lineage":["https://openalex.org/I133837150"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Parkinson","raw_affiliation_strings":["School of Computing and Engineering, University of Huddersfield, Huddersfield, U.K","School of Computing and Engineering, University of Huddersfield, Huddersfield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Huddersfield, Huddersfield, U.K","institution_ids":["https://openalex.org/I133837150"]},{"raw_affiliation_string":"School of Computing and Engineering, University of Huddersfield, Huddersfield, United Kingdom","institution_ids":["https://openalex.org/I133837150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048027692"],"corresponding_institution_ids":["https://openalex.org/I133837150"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.5934,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.89802589,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"134101","last_page":"134114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6133365035057068},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5726301074028015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48498058319091797},{"id":"https://openalex.org/keywords/positron-emission-tomography","display_name":"Positron emission tomography","score":0.4719770848751068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44645795226097107},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.42773541808128357},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3911295235157013},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3429410755634308},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.30483534932136536},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29870909452438354},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.17746299505233765}],"concepts":[{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6133365035057068},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5726301074028015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48498058319091797},{"id":"https://openalex.org/C2775842073","wikidata":"https://www.wikidata.org/wiki/Q208376","display_name":"Positron emission tomography","level":2,"score":0.4719770848751068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44645795226097107},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.42773541808128357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3911295235157013},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3429410755634308},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.30483534932136536},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29870909452438354},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.17746299505233765}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2024.3412850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3412850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/17e6526d-39cf-41c4-9568-0974c44bc92b","is_oa":false,"landing_page_url":"https://pure.hud.ac.uk/en/publications/17e6526d-39cf-41c4-9568-0974c44bc92b","pdf_url":null,"source":{"id":"https://openalex.org/S4306402508","display_name":"Huddersfield Research Portal (University of Huddersfield)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I133837150","host_organization_name":"University of Huddersfield","host_organization_lineage":["https://openalex.org/I133837150"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fakoya, A A & Parkinson, S 2024, 'A Novel Image Casting and Fusion for Identifying Individuals at Risk of Alzheimer\u2019s Disease Using MRI and PET Imaging', IEEE Access, vol. 12, 10552875, pp. 134101-134114. https://doi.org/10.1109/ACCESS.2024.3412850","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:doaj.org/article:57e4409229c447e2bae7bf6a6e176457","is_oa":true,"landing_page_url":"https://doaj.org/article/57e4409229c447e2bae7bf6a6e176457","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 134101-134114 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3412850","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3412850","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1963487177","https://openalex.org/W2028436804","https://openalex.org/W2048468733","https://openalex.org/W2057536936","https://openalex.org/W2071881327","https://openalex.org/W2093602450","https://openalex.org/W2112796928","https://openalex.org/W2146089088","https://openalex.org/W2148726987","https://openalex.org/W2154758450","https://openalex.org/W2159122349","https://openalex.org/W2336579138","https://openalex.org/W2487730443","https://openalex.org/W2592343442","https://openalex.org/W2774698027","https://openalex.org/W2782743885","https://openalex.org/W2792608425","https://openalex.org/W2891326750","https://openalex.org/W2899635607","https://openalex.org/W2901348195","https://openalex.org/W2901966692","https://openalex.org/W2907547898","https://openalex.org/W2940561310","https://openalex.org/W2950619241","https://openalex.org/W2963423764","https://openalex.org/W2966548629","https://openalex.org/W2971066862","https://openalex.org/W2973208504","https://openalex.org/W2982519074","https://openalex.org/W3043995050","https://openalex.org/W3083682961","https://openalex.org/W3111737001","https://openalex.org/W3118922117","https://openalex.org/W3125351044","https://openalex.org/W3183431821","https://openalex.org/W3202902530","https://openalex.org/W3210505114","https://openalex.org/W4224984693","https://openalex.org/W4281826907","https://openalex.org/W4283029781"],"related_works":["https://openalex.org/W3021493803","https://openalex.org/W2257755506","https://openalex.org/W2011111248","https://openalex.org/W4256129901","https://openalex.org/W2002934375","https://openalex.org/W2006468016","https://openalex.org/W2912860444","https://openalex.org/W1907269663","https://openalex.org/W3151415490","https://openalex.org/W2056020138"],"abstract_inverted_index":{"Alzheimer\u2019s":[0],"disease":[1],"(AD)":[2],"is":[3,45,136],"a":[4,28,180,183,238,305,320],"neurodegenerative":[5],"condition":[6,91],"characterised":[7],"by":[8,22,49,319],"permanent":[9],"cognitive":[10,148],"decline.":[11],"The":[12,134,229,271,300],"financial":[13],"burden":[14],"associated":[15],"with":[16,89],"providing":[17],"care":[18],"for":[19,132,142,155,240,246,322],"those":[20],"affected":[21],"this":[23,43,214],"ailment":[24],"has":[25],"escalated":[26],"to":[27,32,47,64,76,102,109,137,151,160,200,233,253,278],"significant":[29],"magnitude,":[30],"amounting":[31],"billions":[33],"of":[34,42,67,86,112,123,129,185,237,262,273,282,315,330],"dollars.":[35],"Moreover,":[36],"projections":[37],"indicate":[38],"that":[39],"the":[40,54,65,84,90,95,110,121,127,139,144,162,189,202,212,235,255,259,263,269,275,280,287,290,295,310,316,323],"prevalence":[41],"sickness":[44],"anticipated":[46],"surge":[48],"more":[50],"than":[51],"200%":[52],"throughout":[53],"next":[55],"15-year":[56],"period.":[57],"Numerous":[58],"researchers":[59],"have":[60],"dedicated":[61],"their":[62,206],"efforts":[63],"field":[66],"computer-aided":[68],"diagnosis":[69],"(CAD),":[70],"whereby":[71],"computational":[72,186],"methods":[73],"are":[74],"used":[75,232,267],"discern":[77],"and":[78,126,169,188,196,222,224,252,285,326],"diagnose":[79],"various":[80],"medical":[81],"conditions.":[82],"Nevertheless,":[83],"identification":[85],"persons":[87],"afflicted":[88],"does":[92],"not":[93,192],"mitigate":[94],"adverse":[96],"consequences.":[97],"It":[98],"would":[99],"be":[100,107,193],"advantageous":[101],"identify":[103],"individuals":[104],"who":[105],"may":[106,191],"susceptible":[108],"onset":[111],"AD":[113,152],"at":[114],"an":[115,328],"early":[116],"stage.":[117],"This":[118],"might":[119],"enhance":[120],"efficacy":[122],"pharmaceutical":[124],"interventions":[125],"implementation":[128],"preventive":[130],"measures":[131],"AD.":[133],"challenge":[135],"determine":[138],"best":[140,199],"method":[141,239],"predicting":[143],"conversion":[145,248],"from":[146,243,258,289],"mild":[147],"impairment":[149],"(MCI)":[150],"while":[153,204,293],"accounting":[154],"two":[156,217,291],"factors:":[157],"(a)":[158],"how":[159,198],"represent":[161],"three-dimensional":[163],"(3D)":[164],"magnetic":[165],"resonance":[166],"imaging":[167,218],"(MRI)":[168],"positron":[170],"emission":[171],"tomography":[172],"(PET)":[173],"images,":[174],"since":[175],"processing":[176],"these":[177],"images":[178,203,251],"takes":[179],"long":[181],"time,":[182],"lot":[184],"power,":[187],"accuracy":[190,296,329],"very":[194],"good;":[195],"(b)":[197],"combine":[201,254],"maintaining":[205],"individual":[207],"image":[208,301],"information.":[209],"To":[210],"solve":[211],"problem,":[213],"research":[215],"examined":[216],"modalities,":[219],"namely":[220],"MRI":[221],"PET,":[223],"convolutional":[225],"neural":[226],"networks":[227],"(CNNs).":[228],"modalities":[230,264,292],"were":[231],"investigate":[234],"creation":[236],"selecting":[241],"slices":[242],"3D":[244],"scans":[245],"eventual":[247],"into":[249,265],"2D":[250],"imagery":[256],"obtained":[257],"slice":[260],"selection":[261],"one":[266],"in":[268,297,312],"CNNs.":[270],"purpose":[272],"developing":[274],"integration":[276],"was":[277],"tackle":[279],"issue":[281],"insufficient":[283],"data":[284],"retain":[286],"information":[288],"improving":[294],"performance":[298],"simultaneously.":[299],"classification":[302],"process":[303],"demonstrated":[304],"much":[306],"quicker":[307],"performance,":[308],"completing":[309],"test":[311],"just":[313],"0.285%":[314],"time":[317],"needed":[318],"3D-CNN":[321],"identical":[324],"task":[325],"achieving":[327],"94.0%.":[331]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2024-06-12T00:00:00"}