{"id":"https://openalex.org/W3011618377","doi":"https://doi.org/10.1117/12.2549485","title":"Combining deep learning and model-based segmentation for labeled spine CT segmentation","display_name":"Combining deep learning and model-based segmentation for labeled spine CT segmentation","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3011618377","doi":"https://doi.org/10.1117/12.2549485","mag":"3011618377"},"language":"en","primary_location":{"id":"doi:10.1117/12.2549485","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","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/A5044179161","display_name":"Christian Buerger","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christian Buerger","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023425451","display_name":"Jens von Berg","orcid":"https://orcid.org/0000-0002-9164-2273"},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens von Berg","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103428740","display_name":"Astrid Franz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Astrid Franz","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041779890","display_name":"Tobias Klinder","orcid":"https://orcid.org/0000-0003-2479-6720"},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Klinder","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073637436","display_name":"Cristian Lorenz","orcid":"https://orcid.org/0000-0002-3693-4230"},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Cristian Lorenz","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075722670","display_name":"Matthias Lenga","orcid":"https://orcid.org/0000-0003-3771-2012"},"institutions":[{"id":"https://openalex.org/I4210162505","display_name":"Philips (Germany)","ror":"https://ror.org/05san5604","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210122849","https://openalex.org/I4210162505"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Lenga","raw_affiliation_strings":["Philips Research Hamburg (Germany)"],"affiliations":[{"raw_affiliation_string":"Philips Research Hamburg (Germany)","institution_ids":["https://openalex.org/I4210162505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044179161"],"corresponding_institution_ids":["https://openalex.org/I4210162505"],"apc_list":null,"apc_paid":null,"fwci":0.9442,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.71414391,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":1.0,"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":1.0,"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":0.9812999963760376,"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":0.9794999957084656,"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/segmentation","display_name":"Segmentation","score":0.8231068849563599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.770675539970398},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7649332880973816},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407026052474976},{"id":"https://openalex.org/keywords/vertebra","display_name":"Vertebra","score":0.6250571012496948},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5567545294761658},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49457404017448425},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4715338349342346},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4322768449783325},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4291396737098694},{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.4250553548336029},{"id":"https://openalex.org/keywords/anatomy","display_name":"Anatomy","score":0.1822972297668457},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.0730561912059784}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8231068849563599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.770675539970398},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7649332880973816},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407026052474976},{"id":"https://openalex.org/C2776412215","wikidata":"https://www.wikidata.org/wiki/Q180323","display_name":"Vertebra","level":2,"score":0.6250571012496948},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5567545294761658},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49457404017448425},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4715338349342346},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4322768449783325},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4291396737098694},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.4250553548336029},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.1822972297668457},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0730561912059784},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2549485","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2549485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2020: Image Processing","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":0,"referenced_works":[],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W183202219","https://openalex.org/W3095877357","https://openalex.org/W2072565696","https://openalex.org/W2050451745","https://openalex.org/W2378903222"],"abstract_inverted_index":{"Automatic":[0],"instance":[1,76],"segmentation":[2,22,72,112,126,187,198],"of":[3,32,38,52,113,130,209],"individual":[4,128],"vertebrae":[5,133,161,176],"from":[6,147,166,179,189],"3D":[7],"CT":[8],"is":[9,40],"essential":[10],"for":[11,63,67,78],"various":[12],"applications":[13],"in":[14,151],"orthopedics,":[15],"neurology,":[16],"and":[17,66,80,116,134,143,169,199,203,217],"oncology.":[18],"In":[19,88,102,138,154],"case":[20],"model-based":[21],"(MBS)":[23],"shall":[24],"be":[25],"used":[26],"to":[27,42,48,58,73,97,122,173],"generate":[28,74,123],"a":[29,35,85,93,118,124],"mesh-based":[30],"representation":[31],"the":[33,49,100,110,148,164,171,174],"spine,":[34],"good":[36],"initialization":[37,65],"MBS":[39,64,70,160],"crucial":[41],"avoid":[43],"wrong":[44],"vertebra":[45,135],"labels":[46],"due":[47],"similar":[50],"appearance":[51],"adjacent":[53],"vertebrae.":[54,218],"Here,":[55],"we":[56,91,105,141,157],"propose":[57,84],"use":[59],"deep":[60],"learning":[61],"(DL)":[62],"robustly":[68],"guiding":[69],"during":[71],"24":[75],"segmentations":[77],"each":[79],"every":[81],"vertebra.":[82],"We":[83,182,193],"four-step":[86],"approach:":[87],"step":[89,103,114,139,152,155,167,180],"1,":[90],"apply":[92,117],"first":[94],"single-class":[95],"U-Net":[96],"coarsely":[98],"segment":[99],"spine.":[101],"2,":[104],"sample":[106],"image":[107],"patches":[108],"along":[109],"coarse":[111],"1":[115],"second":[119],"multi-class":[120],"U-net":[121],"fine":[125],"including":[127],"labeling":[129],"some":[131],"key":[132],"body":[136],"landmarks.":[137],"3,":[140],"detect":[142],"label":[144],"landmark":[145],"coordinates":[146],"classes":[149],"estimated":[150],"2.":[153,181],"4,":[156],"initialize":[158],"all":[159,215],"models":[162],"using":[163],"landmarks":[165],"3":[168],"adapt":[170],"model":[172],"joint":[175],"probability":[177],"map":[178],"validated":[183],"our":[184],"method":[185],"on":[186],"results":[188],"147":[190],"patient":[191],"images.":[192],"computed":[194],"surface":[195],"distances":[196,208],"between":[197],"ground":[200],"truth":[201],"meshes":[202],"achieved":[204],"root":[205],"mean":[206],"squared":[207],"RMSDist":[210],"=":[211],"0.90":[212],"mm":[213],"over":[214],"cases":[216]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
