{"id":"https://openalex.org/W3133402851","doi":"https://doi.org/10.1109/access.2021.3061090","title":"Learning-Based Coronal Spine Alignment Prediction Using Smartphone-Acquired Scoliosis Radiograph Images","display_name":"Learning-Based Coronal Spine Alignment Prediction Using Smartphone-Acquired Scoliosis Radiograph Images","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3133402851","doi":"https://doi.org/10.1109/access.2021.3061090","mag":"3133402851"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3061090","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061090","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360628.pdf","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://ieeexplore.ieee.org/ielx7/6287639/9312710/09360628.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100372506","display_name":"Teng Zhang","orcid":"https://orcid.org/0000-0002-5310-8766"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Teng Zhang","raw_affiliation_strings":["The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355218","display_name":"Yifei Li","orcid":"https://orcid.org/0000-0002-3096-4287"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yifei Li","raw_affiliation_strings":["The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050846738","display_name":"Jason Pui Yin Cheung","orcid":"https://orcid.org/0000-0002-7052-0875"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jason Pui Yin Cheung","raw_affiliation_strings":["The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049381733","display_name":"Socrates Dokos","orcid":"https://orcid.org/0000-0002-7399-2712"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Socrates Dokos","raw_affiliation_strings":["Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109582975","display_name":"Kenneth K. Wong","orcid":"https://orcid.org/0000-0001-8560-9007"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kwan-Yee K. Wong","raw_affiliation_strings":["The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100372506"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.5546,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.95470493,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"38287","last_page":"38295"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11030","display_name":"Scoliosis diagnosis and treatment","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11030","display_name":"Scoliosis diagnosis and treatment","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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":0.9987000226974487,"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/T10776","display_name":"Spinal Fractures and Fixation Techniques","score":0.9761000275611877,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/landmark","display_name":"Landmark","score":0.7696940898895264},{"id":"https://openalex.org/keywords/scoliosis","display_name":"Scoliosis","score":0.7039934396743774},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6911104917526245},{"id":"https://openalex.org/keywords/coronal-plane","display_name":"Coronal plane","score":0.6752195954322815},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5768236517906189},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.5177909135818481},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4776674211025238},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4635099470615387},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4498887062072754},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43799322843551636},{"id":"https://openalex.org/keywords/dicom","display_name":"DICOM","score":0.4278220236301422},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42047780752182007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4106563329696655},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.28419560194015503},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2567380666732788},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.2071416974067688},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1159788966178894}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.7696940898895264},{"id":"https://openalex.org/C2780955175","wikidata":"https://www.wikidata.org/wiki/Q174857","display_name":"Scoliosis","level":2,"score":0.7039934396743774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6911104917526245},{"id":"https://openalex.org/C13483470","wikidata":"https://www.wikidata.org/wiki/Q1470152","display_name":"Coronal plane","level":2,"score":0.6752195954322815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5768236517906189},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.5177909135818481},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4776674211025238},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4635099470615387},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4498887062072754},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43799322843551636},{"id":"https://openalex.org/C77331912","wikidata":"https://www.wikidata.org/wiki/Q81095","display_name":"DICOM","level":2,"score":0.4278220236301422},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42047780752182007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4106563329696655},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28419560194015503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2567380666732788},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.2071416974067688},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1159788966178894},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3061090","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061090","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360628.pdf","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:doaj.org/article:1229b95cbde64a3bba47aad455fb3c4b","is_oa":true,"landing_page_url":"https://doaj.org/article/1229b95cbde64a3bba47aad455fb3c4b","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 38287-38295 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3061090","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061090","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09360628.pdf","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":[{"id":"https://openalex.org/G1808045802","display_name":null,"funder_award_id":"ITS/404/18","funder_id":"https://openalex.org/F4320326427","funder_display_name":"Innovation and Technology Fund"},{"id":"https://openalex.org/G5438714670","display_name":null,"funder_award_id":"AOSEA(R)2019-06","funder_id":"https://openalex.org/F4320321439","funder_display_name":"AOSpine"}],"funders":[{"id":"https://openalex.org/F4320321439","display_name":"AOSpine","ror":"https://ror.org/04mxp4k39"},{"id":"https://openalex.org/F4320326427","display_name":"Innovation and Technology Fund","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3133402851.pdf","grobid_xml":"https://content.openalex.org/works/W3133402851.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W87014095","https://openalex.org/W178718032","https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1969265440","https://openalex.org/W1969973213","https://openalex.org/W2000276621","https://openalex.org/W2001770256","https://openalex.org/W2004376257","https://openalex.org/W2021761973","https://openalex.org/W2049319924","https://openalex.org/W2050366158","https://openalex.org/W2107694226","https://openalex.org/W2136391815","https://openalex.org/W2142568044","https://openalex.org/W2158785895","https://openalex.org/W2164445038","https://openalex.org/W2286479338","https://openalex.org/W2288557819","https://openalex.org/W2289583994","https://openalex.org/W2555751471","https://openalex.org/W2566561901","https://openalex.org/W2618019088","https://openalex.org/W2751970356","https://openalex.org/W2761801613","https://openalex.org/W2803954248","https://openalex.org/W2891120039","https://openalex.org/W2898193142","https://openalex.org/W2902508544","https://openalex.org/W2916452242","https://openalex.org/W2916798096","https://openalex.org/W2922159377","https://openalex.org/W2952819818","https://openalex.org/W2964121744","https://openalex.org/W2968439290","https://openalex.org/W6607209616","https://openalex.org/W6631190155","https://openalex.org/W6639824700","https://openalex.org/W6680285999","https://openalex.org/W6730410022"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2026924879","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W2910159991"],"abstract_inverted_index":{"DICOM":[0],"X-rays":[1,52,193],"are":[2,16],"not":[3,17],"easily":[4],"accessible":[5],"for":[6,68,85,178],"telemedicine,":[7],"and":[8,49,78,80,106,137,148,173,196,205,235,238],"existing":[9],"learning-based":[10],"automated":[11,26],"Cobb":[12],"angle":[13],"(CA)":[14],"predictions":[15],"accurate":[18],"on":[19,37,191],"suboptimal":[20],"X-ray":[21],"images.":[22],"To":[23],"develop":[24],"an":[25],"CA":[27],"prediction":[28],"system":[29],"irrespective":[30,215],"of":[31,90,98,108,117,140,201,212,216],"image":[32,217],"quality,":[33],"with":[34,63,127,158,165,230],"no":[35],"restrictions":[36],"curve":[38],"patterns,":[39],"367":[40],"consecutive":[41],"patients":[42],"attending":[43],"our":[44],"scoliosis":[45],"clinic":[46],"were":[47,53,93,111,124,145,154],"recruited":[48],"their":[50],"coronal":[51],"re-captured":[54],"using":[55],"mobile":[56],"phones.":[57],"Five-fold":[58],"cross-validation":[59],"was":[60,171,176],"conducted":[61],"(each":[62],"294":[64],"randomly":[65],"selected":[66],"images":[67,84],"training":[69],"a":[70],"neural":[71],"network":[72],"SpineHRNet":[73],"to":[74,95,113,194,232],"detect":[75],"endplate":[76,199],"landmarks":[77,92,144,200],"end-vertebrae,":[79],"the":[81,99,115,118,138,141,167,179,188,202,207,213],"remaining":[82],"73":[83],"testing).":[86],"The":[87,133,151],"predicted":[88,119,152,180],"heatmaps":[89],"vertebral":[91],"visualized":[94],"enhance":[96],"interpretability":[97],"SpineHRNet.":[100],"Per-landmark":[101],"Euclidean":[102],"distance":[103],"(L2)":[104],"errors":[105],"recall":[107,139],"landmark":[109],"detection":[110],"calculated":[112],"assess":[114],"accuracy":[116],"landmarks.":[120],"Further":[121],"computed":[122],"CAs":[123,153,181,208],"quantitatively":[125],"compared":[126],"spine-specialists":[128],"measured":[129],"ground":[130],"truth":[131],"(GT).":[132],"average":[134],"L2":[135],"error":[136,170],"detected":[142],"endplates":[143],"2.8":[146],"pixels":[147],"0.99":[149],"respectively.":[150],"all":[155],"significantly":[156],"correlated":[157],"GT":[159],"($\\text{p}":[160],"<;":[161],"0.01$":[162],").":[163],"Compared":[164],"GT,":[166],"mean":[168],"absolute":[169],"3.73-4.15\u00b0":[172],"standard":[174],"deviation":[175],"0.8-1.7\u00b0":[177],"at":[182,209],"different":[183,210],"spinal":[184],"regions.":[185],"This":[186],"is":[187,221],"first":[189],"study":[190],"non-original":[192],"automatically":[195],"accurately":[197],"predict":[198],"scoliotic":[203],"spine":[204],"compute":[206],"regions":[211],"spine,":[214],"qualities.":[218],"SpineHRNet's":[219],"applicability":[220],"evidenced":[222],"by":[223],"five-fold":[224],"cross-validations,":[225],"which":[226],"may":[227],"be":[228],"used":[229],"telemedicine":[231],"facilitate":[233],"fast":[234],"reliable":[236],"auto-diagnosis":[237],"follow-up.":[239]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}