{"id":"https://openalex.org/W4413867401","doi":"https://doi.org/10.32604/cmc.2025.067226","title":"Attention U-Net for Precision Skeletal Segmentation in Chest X-Ray Imaging: Advancing Person Identification Techniques in Forensic Science","display_name":"Attention U-Net for Precision Skeletal Segmentation in Chest X-Ray Imaging: Advancing Person Identification Techniques in Forensic Science","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413867401","doi":"https://doi.org/10.32604/cmc.2025.067226"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.067226","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067226","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.067226","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068796159","display_name":"Hazem Farah","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hazem Farah","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018360551","display_name":"Akram Bennour","orcid":"https://orcid.org/0000-0002-3185-8806"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akram Bennour","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035963088","display_name":"Hama Soltani","orcid":"https://orcid.org/0000-0001-7256-7100"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hama Soltani","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052792812","display_name":"Mouaaz Nahas","orcid":"https://orcid.org/0000-0002-1520-4431"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mouaaz Nahas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018746594","display_name":"Rashiq Rafiq Marie","orcid":"https://orcid.org/0009-0000-2682-8568"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rashiq Rafiq Marie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018844842","display_name":"Mohammed Al-Sarem","orcid":"https://orcid.org/0000-0001-7172-8224"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammed Al-Sarem","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5068796159"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3131,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83202294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"85","issue":"2","first_page":"3335","last_page":"3348"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9883999824523926,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9883999824523926,"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/T12296","display_name":"Autopsy Techniques and Outcomes","score":0.96670001745224,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9300000071525574,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/identification","display_name":"Identification (biology)","score":0.6094653606414795},{"id":"https://openalex.org/keywords/forensic-identification","display_name":"Forensic identification","score":0.5663378238677979},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.45230650901794434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4313303828239441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3900916278362274},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3770851492881775},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3258250951766968},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.30271366238594055},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11968007683753967},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.06018298864364624}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6094653606414795},{"id":"https://openalex.org/C2780732888","wikidata":"https://www.wikidata.org/wiki/Q2314618","display_name":"Forensic identification","level":2,"score":0.5663378238677979},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.45230650901794434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4313303828239441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3900916278362274},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3770851492881775},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3258250951766968},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.30271366238594055},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11968007683753967},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.06018298864364624},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.067226","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067226","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.067226","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.067226","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W262658401","https://openalex.org/W2077067951","https://openalex.org/W2129478881","https://openalex.org/W2179053746","https://openalex.org/W2213792642","https://openalex.org/W2527728540","https://openalex.org/W2945454497","https://openalex.org/W3043595849","https://openalex.org/W3169465625","https://openalex.org/W3213648838","https://openalex.org/W4233018749","https://openalex.org/W4285735529","https://openalex.org/W4383816877","https://openalex.org/W4386854514","https://openalex.org/W4388145582","https://openalex.org/W4400227822","https://openalex.org/W4401315204","https://openalex.org/W4401315240","https://openalex.org/W4401616990","https://openalex.org/W4404692398"],"related_works":["https://openalex.org/W2898732673","https://openalex.org/W4379231730","https://openalex.org/W2410053581","https://openalex.org/W4390692828","https://openalex.org/W2393972099","https://openalex.org/W2272272381","https://openalex.org/W4388147901","https://openalex.org/W2373034544","https://openalex.org/W2197374682","https://openalex.org/W3165940456"],"abstract_inverted_index":{"This":[0,185],"study":[1,96],"presents":[2],"an":[3,94,106],"advanced":[4],"method":[5,60],"for":[6,67,190,204],"post-mortem":[7,205],"person":[8,158],"identification":[9],"using":[10,127],"the":[11,24,87,163,174,188],"segmentation":[12,35,83,124,170],"of":[13,89,108,165,176],"skeletal":[14,48],"structures":[15,49,145],"from":[16],"chest":[17,120,177],"X-ray":[18,121],"images.":[19],"The":[20,70,142],"proposed":[21],"approach":[22],"employs":[23],"Attention":[25,98],"U-Net":[26,99],"architecture,":[27],"enhanced":[28],"with":[29,78,100,123],"gated":[30],"attention":[31,79,103,166],"mechanisms,":[32,104],"to":[33,56,149],"refine":[34],"by":[36],"emphasizing":[37],"spatially":[38],"relevant":[39],"anatomical":[40],"features":[41],"while":[42],"suppressing":[43],"irrelevant":[44],"details.":[45],"By":[46],"isolating":[47],"which":[50],"remain":[51],"stable":[52],"over":[53,135],"time":[54],"compared":[55],"soft":[57],"tissues,":[58],"this":[59],"leverages":[61],"bones":[62],"as":[63],"reliable":[64,202],"biometric":[65,152],"markers":[66],"identity":[68],"verification.":[69],"model":[71],"integrates":[72],"custom-designed":[73],"encoder":[74],"and":[75,101,113,131,138,156,172,182,201],"decoder":[76],"blocks":[77],"gates,":[80],"achieving":[81,134],"high":[82],"precision.":[84],"To":[85],"evaluate":[86],"impact":[88],"architectural":[90],"choices,":[91],"we":[92],"conducted":[93],"ablation":[95],"comparing":[97],"without":[102],"alongside":[105],"analysis":[107],"data":[109],"augmentation":[110],"effects.":[111],"Training":[112],"evaluation":[114],"were":[115,146],"performed":[116],"on":[117],"a":[118,199],"curated":[119],"dataset,":[122],"performance":[125],"measured":[126],"Dice":[128,140],"score,":[129],"precision,":[130],"loss":[132],"functions,":[133],"98%":[136],"precision":[137],"94%":[139],"score.":[141],"extracted":[143],"bone":[144],"further":[147],"processed":[148],"derive":[150],"unique":[151],"patterns,":[153],"enabling":[154],"robust":[155],"privacy-preserving":[157],"identification.":[159,206],"Our":[160],"findings":[161],"highlight":[162],"effectiveness":[164],"mechanisms":[167],"in":[168,180],"improving":[169],"accuracy":[171],"underscore":[173],"potential":[175],"bone-based":[178],"biometrics":[179],"forensic":[181,196],"medical":[183],"imaging.":[184],"work":[186],"paves":[187],"way":[189],"integrating":[191],"artificial":[192],"intelligence":[193],"into":[194],"real-world":[195],"workflows,":[197],"offering":[198],"non-invasive":[200],"solution":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}