{"id":"https://openalex.org/W4399885189","doi":"https://doi.org/10.3233/ida-240431","title":"Bone feature quantization and systematized attention gate UNet-based deep learning framework for bone fracture classification","display_name":"Bone feature quantization and systematized attention gate UNet-based deep learning framework for bone fracture classification","publication_year":2024,"publication_date":"2024-06-21","ids":{"openalex":"https://openalex.org/W4399885189","doi":"https://doi.org/10.3233/ida-240431"},"language":"en","primary_location":{"id":"doi:10.3233/ida-240431","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-240431","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052173305","display_name":"M. Shyamala Devi","orcid":"https://orcid.org/0000-0001-6118-389X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M Shyamala Devi","raw_affiliation_strings":["Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108735924","display_name":"R. Aruna","orcid":null},"institutions":[{"id":"https://openalex.org/I1330855593","display_name":"Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology","ror":"https://ror.org/05bc5bx80","country_code":"IN","type":"education","lineage":["https://openalex.org/I1330855593"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R Aruna","raw_affiliation_strings":["Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&amp;D Institute of Science and Technology, Chennai, India","Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&amp;D Institute of Science and Technology, Chennai, India","institution_ids":["https://openalex.org/I1330855593"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India","institution_ids":["https://openalex.org/I1330855593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006889663","display_name":"Saman M. Almufti\u200e","orcid":"https://orcid.org/0000-0002-1843-745X"},"institutions":[{"id":"https://openalex.org/I4210146391","display_name":"Nawroz University","ror":"https://ror.org/04gp75d48","country_code":"IQ","type":"education","lineage":["https://openalex.org/I4210146391"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Saman Almufti","raw_affiliation_strings":["Department of Computer Science, Nawroz University, Duhok, Kurdistan Region, Iraq"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nawroz University, Duhok, Kurdistan Region, Iraq","institution_ids":["https://openalex.org/I4210146391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040290767","display_name":"P. Punitha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"P Punitha","raw_affiliation_strings":["Department of Artificial Intelligence and Data Science, Tagore Institute of Engineering and Technology, Salem, India"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Data Science, Tagore Institute of Engineering and Technology, Salem, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071124185","display_name":"R. Lakshmana Kumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R Lakshmana Kumar","raw_affiliation_strings":["Department of Artificial Intelligence and Machine Learning, Tagore Institute of Engineering and Technology, Salem, India"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence and Machine Learning, Tagore Institute of Engineering and Technology, Salem, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052173305"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9351,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.91278581,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":"2","first_page":"513","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9984999895095825,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9984999895095825,"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"}},{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/feature","display_name":"Feature (linguistics)","score":0.5821300745010376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5621663928031921},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5575194954872131},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5181192755699158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4215216040611267},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.18021628260612488}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5821300745010376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5621663928031921},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5575194954872131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5181192755699158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4215216040611267},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.18021628260612488},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-240431","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-240431","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis: An International Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1502235192","https://openalex.org/W1862397562","https://openalex.org/W1963750971","https://openalex.org/W1972142489","https://openalex.org/W2101087183","https://openalex.org/W2183341477","https://openalex.org/W2346062110","https://openalex.org/W2465708929","https://openalex.org/W2531409750","https://openalex.org/W2561981131","https://openalex.org/W2733840449","https://openalex.org/W2752566774","https://openalex.org/W2752747624","https://openalex.org/W2776581140","https://openalex.org/W2790565150","https://openalex.org/W2793251588","https://openalex.org/W2800043213","https://openalex.org/W2811095288","https://openalex.org/W2962860144","https://openalex.org/W2963446712","https://openalex.org/W2963521553","https://openalex.org/W2964566283","https://openalex.org/W2993088948","https://openalex.org/W3007969083","https://openalex.org/W3013598351","https://openalex.org/W3099409464","https://openalex.org/W3100175985","https://openalex.org/W3103371431","https://openalex.org/W3125296229","https://openalex.org/W3134492315","https://openalex.org/W3138118097","https://openalex.org/W3160035121","https://openalex.org/W3161761924","https://openalex.org/W3164925041","https://openalex.org/W3209504874","https://openalex.org/W3211975597","https://openalex.org/W4205476689","https://openalex.org/W4285821790","https://openalex.org/W4292260733","https://openalex.org/W4312726348","https://openalex.org/W4313289412","https://openalex.org/W4319068839","https://openalex.org/W4320155875","https://openalex.org/W4386981297","https://openalex.org/W4387737920","https://openalex.org/W4391012053","https://openalex.org/W4391164186","https://openalex.org/W4393105607","https://openalex.org/W4394625351"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W4386159726"],"abstract_inverted_index":{"Bones":[0],"collaborate":[1],"with":[2,49,92,119,155,234,269,326,428,483],"muscles":[3],"and":[4,8,21,26,53,82,181,220,248,317],"joints":[5],"to":[6,34,58,71,96,104,183,199,251,285,356,377,404,417,421,448,458,490],"sustain":[7],"maintain":[9],"our":[10],"freedom":[11],"of":[12,18,66,116,125,168,174,188,227,266,272,290,304,346,386,462,487],"mobility.":[13],"The":[14,63,122,130,151,171,191,208,229,301,320,437,467],"proper":[15,86],"musculoskeletal":[16],"activity":[17],"bone":[19,31,67,98,117,169,267,276,480],"protects":[20],"strengthens":[22],"the":[23,50,114,145,157,165,175,184,202,225,235,253,264,280,287,291,298,305,309,313,331,335,340,343,350,358,361,366,370,379,383,387,406,418,423,434,450,459,463,472,479,491],"brain,":[24],"heart,":[25],"lung":[27],"function.":[28],"When":[29],"a":[30,35,106,484],"is":[32,128,179,323,354,375,456],"subjected":[33],"force":[36],"greater":[37],"than":[38],"its":[39],"structural":[40],"capacity,":[41],"it":[42],"fractures.":[43],"Bone":[44,193],"fractures":[45,99,268],"should":[46,54],"be":[47,55,90],"detected":[48],"appropriate":[51],"type":[52,115],"treated":[56],"early":[57],"avoid":[59],"acute":[60],"neurovascular":[61],"complications.":[62],"manual":[64],"detection":[65],"fracture":[68,118,481],"may":[69],"lead":[70],"highly":[72],"delayed":[73],"complications":[74],"like":[75,239],"malunion,":[76],"Joint":[77],"stiffness,":[78],"Contractures,":[79],"Myositis":[80],"ossificans,":[81],"Avascular":[83],"necrosis.":[84],"A":[85],"classification":[87,265],"system":[88],"must":[89],"integrated":[91],"deep":[93,475,493],"learning":[94,142,159,365,476,494],"technology":[95],"classify":[97],"accurately.":[100],"This":[101,412],"motivates":[102],"me":[103],"propose":[105],"Systematized":[107],"Attention":[108,160,176,189,249,261,281,288,302],"Gate":[109,303],"UNet":[110,161,177,247,250,262,282],"(SAG-UNet)":[111],"that":[112,163,260,295,329,471],"classifies":[113,164,478],"high":[120,485],"accuracy.":[121],"main":[123],"contribution":[124,132,153],"this":[126],"research":[127],"two-fold.":[129],"first":[131],"focuses":[133],"on":[134,342],"dataset":[135,196],"preprocessing":[136],"through":[137],"feature":[138,211,315,347,371,388,410,426,440],"extraction":[139],"using":[140,205,445],"unsupervised":[141],"by":[143],"adapting":[144],"Growing":[146],"Neural":[147],"Gas":[148],"(GNG)":[149],"method.":[150],"second":[152],"deals":[154],"refining":[156],"supervised":[158],"model":[162,178,477],"ten":[166],"types":[167,482],"fracture.":[170],"attention":[172,409,424,438,452],"gate":[173,289,318],"refined":[180],"applied":[182,355,416],"upsampling":[185,293],"decoding":[186,465],"layer":[187,294],"UNet.":[190],"KAGGLE":[192],"Break":[194],"Classification":[195],"was":[197,215,283,402,442],"processed":[198,325],"extract":[200],"only":[201],"essential":[203],"features":[204,333],"GNG":[206],"extraction.":[207],"quantized":[209],"significant":[210],"RGB":[212],"X-ray":[213],"image":[214],"divided":[216],"into":[217],"900":[218],"training":[219,230],"230":[221],"testing":[222,275],"images":[223,231],"in":[224,334,360,369,382],"ratio":[226],"80:20.":[228],"are":[232],"fitted":[233],"existing":[236,492],"CNN":[237,255],"models":[238],"DenseNet,":[240],"VGG,":[241],"AlexNet,":[242],"MobileNet,":[243],"EfficientNet,":[244],"Inception,":[245],"Xception,":[246],"choose":[252],"best":[254],"model.":[256],"Experiment":[257],"results":[258,469],"portray":[259],"offers":[263],"an":[270],"accuracy":[271,486],"89%":[273],"when":[274],"break":[277],"images.":[278],"Now,":[279],"chosen":[284],"refine":[286],"Decoding":[292],"occurs":[296],"after":[297],"encoding":[299],"layer.":[300,466],"proposed":[306,473],"SAG-UNet":[307,474],"forms":[308],"gating":[310,321],"coefficient":[311,322,425,439],"from":[312],"input":[314],"map":[316,427,441],"signal.":[319],"then":[324],"batch":[327],"normalization":[328],"centers":[330],"aligned":[332,362,384,435],"active":[336],"region,":[337],"thereby":[338,364],"leaving":[339],"focus":[341],"unaligned":[344],"weights":[345,385,429],"maps.":[348],"Then,":[349,373,390],"ReLU":[351],"activation":[352,420],"function":[353],"introduce":[357],"nonlinearity":[359],"features,":[363],"complex":[367],"representation":[368],"vector.":[372],"dropout":[374],"used":[376],"exclude":[378],"error":[380],"noise":[381],"map.":[389,411],"1":[391,398],"<mml:math":[392],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[393],"display=\"inline\"":[394],"overflow=\"scroll\">":[395],"<mml:mo>\u00d7</mml:mo>":[396],"</mml:math>":[397],"linear":[399],"convolution":[400],"transformation":[401],"done":[403],"form":[405,449],"vector":[407,413],"concatenation-based":[408],"has":[414],"been":[415],"sigmoid":[419],"create":[422],"assigned":[430],"as":[431],"\u20181\u2019":[432],"for":[433],"features.":[436],"grid":[443],"resampled":[444],"trilinear":[446],"interpolation":[447],"spatial":[451],"weight":[453],"map,":[454],"which":[455],"passed":[457],"skip":[460],"connection":[461],"next":[464],"implementation":[468],"reveal":[470],"98.78%":[488],"compared":[489],"models.":[495]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}