{"id":"https://openalex.org/W4408355124","doi":"https://doi.org/10.1109/icassp49660.2025.10889899","title":"Incorporating Improved Sinusoidal Threshold-based Semi-supervised Method and Diffusion Models for Osteoporosis Diagnosis","display_name":"Incorporating Improved Sinusoidal Threshold-based Semi-supervised Method and Diffusion Models for Osteoporosis Diagnosis","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355124","doi":"https://doi.org/10.1109/icassp49660.2025.10889899"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022084435","display_name":"Wenchi Ke","orcid":"https://orcid.org/0009-0008-2857-7596"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenchi Ke","raw_affiliation_strings":["Sichuan University,College of Computer Science,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357677","display_name":"Hu Chen","orcid":"https://orcid.org/0000-0001-9300-6572"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Chen","raw_affiliation_strings":["Sichuan University,College of Computer Science,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100388188","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-5867-9322"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Sichuan University,Key Laboratory of Data Protection and Intelligent Management,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,Key Laboratory of Data Protection and Intelligent Management,China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082236554","display_name":"Xiong Deng","orcid":"https://orcid.org/0000-0002-5207-471X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiong Deng","raw_affiliation_strings":["Stevens Institute of Technology,Computer Science Department,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology,Computer Science Department,USA","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9610000252723694,"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.9610000252723694,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/osteoporosis","display_name":"Osteoporosis","score":0.5844379663467407},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5843228101730347},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5037516951560974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3523401916027069},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18110784888267517},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08318090438842773}],"concepts":[{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.5844379663467407},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5843228101730347},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5037516951560974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3523401916027069},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18110784888267517},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08318090438842773},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889899","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1969874082","https://openalex.org/W1980550139","https://openalex.org/W2015178646","https://openalex.org/W2052113230","https://openalex.org/W2110396808","https://openalex.org/W2194775991","https://openalex.org/W2599867508","https://openalex.org/W2963446712","https://openalex.org/W2964137095","https://openalex.org/W3003905048","https://openalex.org/W3042471642","https://openalex.org/W3043151376","https://openalex.org/W3095910727","https://openalex.org/W3185110941","https://openalex.org/W4283661653","https://openalex.org/W4297022515","https://openalex.org/W4312436424","https://openalex.org/W4376466809","https://openalex.org/W6637373629","https://openalex.org/W6773005947","https://openalex.org/W6779823529","https://openalex.org/W6788329692","https://openalex.org/W6839041728"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Osteoporosis":[0],"is":[1,119],"a":[2,94,122,137],"common":[3],"skeletal":[4],"disease":[5],"that":[6],"seriously":[7],"affects":[8],"patients\u2019":[9],"quality":[10],"of":[11,50],"life.":[12],"Traditional":[13],"osteoporosis":[14,40],"diagnosis":[15],"methods":[16],"are":[17,68],"expensive":[18],"and":[19,28,53,112,129,135],"complex.":[20],"The":[21],"semi-supervised":[22,58,107],"model":[23,27,85,108],"based":[24,41],"on":[25,42,121],"diffusion":[26,72,84],"class":[29],"threshold":[30,97],"sinusoidal":[31],"decay":[32],"proposed":[33],"in":[34,65],"this":[35,66,91],"paper":[36,67,92],"can":[37,104],"automatically":[38],"diagnose":[39],"patient\u2019s":[43],"imaging":[44],"data,":[45,78],"which":[46,103],"has":[47],"the":[48,61,71,83,106,117],"advantages":[49],"convenience,":[51],"accuracy,":[52],"low":[54],"cost.":[55],"Unlike":[56],"previous":[57],"models,":[59],"all":[60],"unlabeled":[62,77],"data":[63,80],"used":[64],"generated":[69,81],"by":[70,82],"model.":[73],"Compared":[74],"with":[75],"real":[76],"synthetic":[79],"show":[86],"better":[87],"performance.":[88,115],"In":[89],"addition,":[90],"proposes":[93],"novel":[95],"pseudo-label":[96],"adjustment":[98],"mechanism,":[99],"Sinusoidal":[100],"Threshold":[101],"Decay,":[102],"make":[105],"converge":[109],"more":[110],"quickly":[111],"improve":[113],"its":[114,130],"Specifically,":[116],"method":[118],"tested":[120],"dataset":[123],"including":[124],"749":[125],"dental":[126],"panoramic":[127],"images,":[128],"achieved":[131],"leading":[132],"detect":[133],"performance":[134],"produces":[136],"80.10%":[138],"accuracy.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}