{"id":"https://openalex.org/W3108141192","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263566","title":"An End-to-End Segmentation Network for the Temporomandibular Joints CBCT Image based on 3D U-Net","display_name":"An End-to-End Segmentation Network for the Temporomandibular Joints CBCT Image based on 3D U-Net","publication_year":2020,"publication_date":"2020-10-17","ids":{"openalex":"https://openalex.org/W3108141192","doi":"https://doi.org/10.1109/cisp-bmei51763.2020.9263566","mag":"3108141192"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei51763.2020.9263566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5100323983","display_name":"Kai Zhang","orcid":"https://orcid.org/0000-0002-6319-3722"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Beijing Jiaotong University,School of Electronics and Information Engineering,Beijing,China","School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,School of Electronics and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024528584","display_name":"Jupeng Li","orcid":"https://orcid.org/0000-0002-2414-7440"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jupeng Li","raw_affiliation_strings":["Beijing Jiaotong University,School of Electronics and Information Engineering,Beijing,China","School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,School of Electronics and Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104221127","display_name":"Ruohan Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210095659","display_name":"Peking University Stomatological Hospital","ror":"https://ror.org/00s2xkh70","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210095659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruohan Ma","raw_affiliation_strings":["Peking University School and Hospital of Stomatology,Department of Oral and Maxillofacial Radiology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Peking University School and Hospital of Stomatology,Department of Oral and Maxillofacial Radiology,Beijing,China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210095659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438653","display_name":"Gang Li","orcid":"https://orcid.org/0000-0001-9585-1382"},"institutions":[{"id":"https://openalex.org/I4210095659","display_name":"Peking University Stomatological Hospital","ror":"https://ror.org/00s2xkh70","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210095659"]},{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["Peking University School and Hospital of Stomatology,Department of Oral and Maxillofacial Radiology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Peking University School and Hospital of Stomatology,Department of Oral and Maxillofacial Radiology,Beijing,China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210095659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100323983"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.1327,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.77251789,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"664","last_page":"668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T11363","display_name":"Dental Radiography and Imaging","score":0.9976000189781189,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9886000156402588,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7726085782051086},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7617210149765015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.716118335723877},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.6248869895935059},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6159141063690186},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.612074613571167},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.5175504088401794},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.5034155249595642},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47367292642593384},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4660065770149231},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.461089551448822},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44563156366348267},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.4374960660934448},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4336439371109009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4006442427635193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1592661440372467}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7726085782051086},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7617210149765015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.716118335723877},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.6248869895935059},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6159141063690186},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.612074613571167},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.5175504088401794},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.5034155249595642},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47367292642593384},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4660065770149231},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.461089551448822},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44563156366348267},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.4374960660934448},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4336439371109009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4006442427635193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1592661440372467},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei51763.2020.9263566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei51763.2020.9263566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 13th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1565402342","https://openalex.org/W1567302070","https://openalex.org/W1842610785","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W2005889048","https://openalex.org/W2022508996","https://openalex.org/W2161237731","https://openalex.org/W2464708700","https://openalex.org/W2517954747","https://openalex.org/W2608353599","https://openalex.org/W2804078698","https://openalex.org/W2894802018","https://openalex.org/W2944904709","https://openalex.org/W2962914239","https://openalex.org/W2982182858","https://openalex.org/W3007028022","https://openalex.org/W3028055348","https://openalex.org/W3035665735","https://openalex.org/W6638650905","https://openalex.org/W6639824700","https://openalex.org/W6640295612","https://openalex.org/W6752378368","https://openalex.org/W6769011258","https://openalex.org/W6777931787"],"related_works":["https://openalex.org/W3104750253","https://openalex.org/W4402926319","https://openalex.org/W4389060404","https://openalex.org/W2973136608","https://openalex.org/W3012828488","https://openalex.org/W4286233748","https://openalex.org/W4254054209","https://openalex.org/W4200334192","https://openalex.org/W4391935352","https://openalex.org/W2952835238"],"abstract_inverted_index":{"The":[0,63],"temporomandibular":[1,19],"joints":[2],"segmentation":[3,50,59,82,112],"from":[4],"CBCT":[5,61,91],"images":[6],"plays":[7],"an":[8,100],"important":[9],"role":[10],"in":[11,60],"medical":[12],"diagnosis":[13],"of":[14,68,84],"related":[15],"diseases,":[16],"such":[17],"as":[18],"disorders.":[20],"However,":[21],"due":[22],"to":[23,72],"the":[24,57,69,80,85,110,115],"weak":[25],"contrast":[26],"and":[27,75,114],"heterogeneous":[28],"shapes,":[29],"this":[30,41],"task":[31],"is":[32],"considerably":[33],"challenging":[34],"for":[35,56],"conventional":[36],"image":[37,92],"processing":[38],"algorithms.":[39],"In":[40],"paper,":[42],"we":[43],"proposed":[44,64,86],"a":[45],"novel":[46],"end-to-end":[47],"deep":[48],"learning":[49],"network":[51,65],"based":[52],"on":[53,88],"3D":[54],"U-Net":[55],"TMJ":[58],"volumes.":[62],"takes":[66],"advantages":[67],"symmetrical":[70],"architecture":[71],"achieve":[73],"precise":[74],"voxel-wise":[76],"prediction.":[77],"We":[78],"demonstrated":[79],"well":[81],"results":[83],"method":[87,98],"our":[89,97],"clinical":[90],"datasets.":[93],"Without":[94],"any":[95],"post-processing,":[96],"attained":[99],"average":[101],"Dice":[102],"Coefficient":[103],"0.9760":[104],"which":[105],"performed":[106],"much":[107],"better":[108],"than":[109],"super-pixel":[111],"algorithm":[113],"active":[116],"contour":[117],"model.":[118]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
