{"id":"https://openalex.org/W2597063270","doi":"https://doi.org/10.1117/12.2254546","title":"Robust segmentation of trabecular bone for <i>in vivo</i> CT imaging using anisotropic diffusion and multi-scale morphological reconstruction","display_name":"Robust segmentation of trabecular bone for <i>in vivo</i> CT imaging using anisotropic diffusion and multi-scale morphological reconstruction","publication_year":2017,"publication_date":"2017-03-13","ids":{"openalex":"https://openalex.org/W2597063270","doi":"https://doi.org/10.1117/12.2254546","mag":"2597063270"},"language":"en","primary_location":{"id":"doi:10.1117/12.2254546","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2254546","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5100420520","display_name":"Cheng Chen","orcid":"https://orcid.org/0000-0001-9424-9365"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cheng Chen","raw_affiliation_strings":["The Univ. of Iowa (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Iowa (United States)","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027768127","display_name":"Dakai Jin","orcid":"https://orcid.org/0000-0002-4806-2943"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dakai Jin","raw_affiliation_strings":["The Univ. of Iowa (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Iowa (United States)","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018595476","display_name":"Xiaoliu Zhang","orcid":"https://orcid.org/0000-0002-2085-3997"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoliu Zhang","raw_affiliation_strings":["The Univ. of Iowa (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Iowa (United States)","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010165489","display_name":"Steven M. Levy","orcid":"https://orcid.org/0000-0001-9150-4199"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven M. Levy","raw_affiliation_strings":["The Univ. of Iowa (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Iowa (United States)","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033203259","display_name":"Punam K. Saha","orcid":"https://orcid.org/0000-0003-1576-118X"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Punam K. Saha","raw_affiliation_strings":["The Univ. of Iowa (United States)"],"affiliations":[{"raw_affiliation_string":"The Univ. of Iowa (United States)","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100420520"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.4166,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63314311,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"10137","issue":null,"first_page":"101371T","last_page":"101371T"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9993000030517578,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9979000091552734,"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/hessian-matrix","display_name":"Hessian matrix","score":0.7046964168548584},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6779924631118774},{"id":"https://openalex.org/keywords/anisotropy","display_name":"Anisotropy","score":0.5951019525527954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347722172737122},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5002739429473877},{"id":"https://openalex.org/keywords/biomedical-engineering","display_name":"Biomedical engineering","score":0.476455956697464},{"id":"https://openalex.org/keywords/osteoporosis","display_name":"Osteoporosis","score":0.46690019965171814},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.4576534032821655},{"id":"https://openalex.org/keywords/fracture","display_name":"Fracture (geology)","score":0.42732110619544983},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4249420762062073},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.42185115814208984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3891175389289856},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.33963918685913086},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26907268166542053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2536942958831787},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20610037446022034},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1486104130744934},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.13328176736831665},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.12051001191139221},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.11482483148574829},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.08342736959457397}],"concepts":[{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.7046964168548584},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6779924631118774},{"id":"https://openalex.org/C85725439","wikidata":"https://www.wikidata.org/wiki/Q466686","display_name":"Anisotropy","level":2,"score":0.5951019525527954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347722172737122},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5002739429473877},{"id":"https://openalex.org/C136229726","wikidata":"https://www.wikidata.org/wiki/Q327092","display_name":"Biomedical engineering","level":1,"score":0.476455956697464},{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.46690019965171814},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.4576534032821655},{"id":"https://openalex.org/C43369102","wikidata":"https://www.wikidata.org/wiki/Q2307625","display_name":"Fracture (geology)","level":2,"score":0.42732110619544983},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4249420762062073},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.42185115814208984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3891175389289856},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33963918685913086},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26907268166542053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2536942958831787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20610037446022034},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1486104130744934},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.13328176736831665},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.12051001191139221},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11482483148574829},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.08342736959457397},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2254546","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2254546","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1964983194","https://openalex.org/W1965930865","https://openalex.org/W1968069998","https://openalex.org/W1969210223","https://openalex.org/W1970215274","https://openalex.org/W1979344569","https://openalex.org/W1982547218","https://openalex.org/W1993457878","https://openalex.org/W2007222931","https://openalex.org/W2009399798","https://openalex.org/W2016550079","https://openalex.org/W2020775263","https://openalex.org/W2040156285","https://openalex.org/W2042426452","https://openalex.org/W2043362084","https://openalex.org/W2048250502","https://openalex.org/W2051391248","https://openalex.org/W2057419293","https://openalex.org/W2059087897","https://openalex.org/W2059996803","https://openalex.org/W2064281076","https://openalex.org/W2070914367","https://openalex.org/W2077498288","https://openalex.org/W2097232421","https://openalex.org/W2102024055","https://openalex.org/W2102295861","https://openalex.org/W2105822769","https://openalex.org/W2106990937","https://openalex.org/W2111064390","https://openalex.org/W2129534965","https://openalex.org/W2138997396","https://openalex.org/W2150134853","https://openalex.org/W2157840858","https://openalex.org/W2159591750","https://openalex.org/W2424606423","https://openalex.org/W2507690070","https://openalex.org/W4206679801","https://openalex.org/W4229750588","https://openalex.org/W4238209133","https://openalex.org/W4240509403","https://openalex.org/W4296492010","https://openalex.org/W6676356933","https://openalex.org/W6679367408","https://openalex.org/W6683266177"],"related_works":["https://openalex.org/W2138983844","https://openalex.org/W1968965685","https://openalex.org/W2012792772","https://openalex.org/W2356573839","https://openalex.org/W2111883783","https://openalex.org/W2009028679","https://openalex.org/W2357424838","https://openalex.org/W2327601824","https://openalex.org/W4237142086","https://openalex.org/W2161102362"],"abstract_inverted_index":{"Osteoporosis":[0],"is":[1,15,22],"associated":[2],"with":[3],"an":[4],"increased":[5],"risk":[6],"of":[7,11,26,57,109],"low-trauma":[8],"fractures.":[9],"Segmentation":[10],"trabecular":[12,58],"bone":[13,27,117],"(TB)":[14],"essential":[16],"to":[17,53],"assess":[18],"TB":[19,39,69,100,111],"microstructure,":[20],"which":[21],"a":[23,35,62],"key":[24],"determinant":[25],"strength":[28,118],"and":[29,76],"fracture":[30],"risk.":[31],"Here,":[32],"we":[33],"present":[34],"new":[36,63,83,104],"method":[37,47,84,105],"for":[38,41,68,81,114],"segmentation":[40,101],"<i>in":[42,91],"vivo</i>":[43,92],"CT":[44,93],"imaging.":[45],"The":[46],"uses":[48],"Hessian":[49],"matrix-guided":[50],"anisotropic":[51],"diffusion":[52],"improve":[54],"local":[55],"separability":[56],"structures,":[59],"followed":[60],"by":[61],"multi-scale":[64],"morphological":[65],"reconstruction":[66],"algorithm":[67],"segmentation.":[70],"High":[71],"sensitivity":[72],"(0.93),":[73,75],"specificity":[74],"accuracy":[77],"(0.92)":[78],"were":[79],"observed":[80],"the":[82,103,107],"based":[85],"on":[86,90],"regional":[87],"manual":[88],"thresholding":[89],"images.":[94],"Mechanical":[95],"tests":[96],"have":[97],"shown":[98],"that":[99],"using":[102],"improved":[106],"ability":[108],"derived":[110],"spacing":[112],"measure":[113],"predicting":[115],"actual":[116],"(R<sup>2</sup>=0.83).":[119]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}