{"id":"https://openalex.org/W3210422252","doi":"https://doi.org/10.1109/mapr53640.2021.9585292","title":"A deep learning based fracture detection in arm bone X-ray images","display_name":"A deep learning based fracture detection in arm bone X-ray images","publication_year":2021,"publication_date":"2021-10-01","ids":{"openalex":"https://openalex.org/W3210422252","doi":"https://doi.org/10.1109/mapr53640.2021.9585292","mag":"3210422252"},"language":"en","primary_location":{"id":"doi:10.1109/mapr53640.2021.9585292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mapr53640.2021.9585292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","raw_type":"proceedings-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/A5026528223","display_name":"Hoai Phuong Nguyen","orcid":"https://orcid.org/0000-0003-3522-3098"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Hoai Phuong Nguyen","raw_affiliation_strings":["School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109533062","display_name":"Thi Phuong Hoang","orcid":null},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Thi Phuong Hoang","raw_affiliation_strings":["School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam","institution_ids":["https://openalex.org/I94518387"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101654553","display_name":"Huy H. Nguyen","orcid":"https://orcid.org/0000-0002-2000-7977"},"institutions":[{"id":"https://openalex.org/I94518387","display_name":"Hanoi University of Science and Technology","ror":"https://ror.org/04nyv3z04","country_code":"VN","type":"education","lineage":["https://openalex.org/I94518387"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Huy Hoang Nguyen","raw_affiliation_strings":["School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam","institution_ids":["https://openalex.org/I94518387"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I94518387"],"apc_list":null,"apc_paid":null,"fwci":1.8682,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.84876698,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9919000267982483,"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":0.9919000267982483,"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":0.9679999947547913,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9606999754905701,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7887071371078491},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7007732391357422},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.626950740814209},{"id":"https://openalex.org/keywords/histogram-equalization","display_name":"Histogram equalization","score":0.608184814453125},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5662827491760254},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5409132242202759},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49973034858703613},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4960807263851166},{"id":"https://openalex.org/keywords/fracture","display_name":"Fracture (geology)","score":0.48500844836235046},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47626087069511414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46923404932022095},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4523324966430664},{"id":"https://openalex.org/keywords/adaptive-histogram-equalization","display_name":"Adaptive histogram equalization","score":0.4427404999732971},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11811023950576782}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7887071371078491},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7007732391357422},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.626950740814209},{"id":"https://openalex.org/C136943445","wikidata":"https://www.wikidata.org/wiki/Q1970240","display_name":"Histogram equalization","level":4,"score":0.608184814453125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5662827491760254},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5409132242202759},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49973034858703613},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4960807263851166},{"id":"https://openalex.org/C43369102","wikidata":"https://www.wikidata.org/wiki/Q2307625","display_name":"Fracture (geology)","level":2,"score":0.48500844836235046},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47626087069511414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46923404932022095},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4523324966430664},{"id":"https://openalex.org/C30387639","wikidata":"https://www.wikidata.org/wiki/Q4680744","display_name":"Adaptive histogram equalization","level":5,"score":0.4427404999732971},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11811023950576782},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mapr53640.2021.9585292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mapr53640.2021.9585292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2031489346","https://openalex.org/W2530686067","https://openalex.org/W2776581140","https://openalex.org/W2803124023","https://openalex.org/W2963718163","https://openalex.org/W2993088948","https://openalex.org/W2993182889","https://openalex.org/W3018757597","https://openalex.org/W3023173618","https://openalex.org/W3047032303","https://openalex.org/W3081754757","https://openalex.org/W3092243440","https://openalex.org/W3106250896","https://openalex.org/W6751554223","https://openalex.org/W6777046832","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W1964281796","https://openalex.org/W2022339659","https://openalex.org/W2101522512","https://openalex.org/W2035413902","https://openalex.org/W3039532712","https://openalex.org/W2136748848","https://openalex.org/W2547556426","https://openalex.org/W4285827401","https://openalex.org/W1983610137","https://openalex.org/W2131911629"],"abstract_inverted_index":{"A":[0],"large":[1],"number":[2],"of":[3,47,82],"arm":[4,29],"fracture-related":[5],"injuries":[6],"are":[7],"reported":[8],"in":[9,28],"hospitals":[10],"and":[11,53,78],"clinics":[12],"around":[13],"the":[14,36,48,80,107,114],"world.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19,34],"propose":[20],"a":[21,45,68],"novel":[22],"deep":[23],"learning":[24],"based":[25,109],"fracture":[26,84],"detection":[27],"bone":[30,83],"X-ray":[31,86],"images.":[32,87],"First,":[33],"preprocess":[35],"Xray":[37],"image":[38,51,60],"by":[39,94],"using":[40,95],"an":[41],"algorithm":[42],"that":[43,103],"is":[44,65,92],"combination":[46],"YOLACT++":[49],"for":[50,59],"segmentation":[52],"Contrast":[54],"Limited":[55],"Adaptive":[56],"Histogram":[57],"Equalization":[58],"contrast":[61],"enhancement.":[62],"Then,":[63],"YOLOv4":[64],"trained":[66],"on":[67,85,113],"small":[69,115],"dataset":[70],"with":[71],"four":[72],"data":[73],"augmentation":[74],"techniques":[75],"to":[76],"identify":[77],"locate":[79],"position":[81],"The":[88],"topmost":[89],"result":[90],"obtained":[91],"81.91%":[93],"our":[96,104],"proposed":[97],"method.":[98],"Experimental":[99],"results":[100],"also":[101],"confirm":[102],"method":[105],"outperforms":[106],"Faster-RCNN":[108],"solution":[110],"while":[111],"implementing":[112],"dataset.":[116]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}