The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa
•CT scan processing protocols should remain consistent for accurate results.•Slight variation (e.g., ∼50 HU) in thresholding does not substantially alter resultant surfaces.•Error generated by scan processing is less than allowable measurement error (1–2mm). As the accessibility and utility of virtu...
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description | •CT scan processing protocols should remain consistent for accurate results.•Slight variation (e.g., ∼50 HU) in thresholding does not substantially alter resultant surfaces.•Error generated by scan processing is less than allowable measurement error (1–2mm).
As the accessibility and utility of virtual databases of skeletal collections continues to grow, the impact that scan processing procedures has on the accuracy of data obtained from virtual databases remains relatively unknown. This study quantifies the intra- and inter-observer error generated from varying computed tomography (CT) scan processing protocols, including re-segmentation, incrementally varying thresholding value, and data collectors’ selection of the threshold value on a set of virtual subadult pelves. Four observers segmented the subadult ossa coxarum from postmortem CT scans of the fully-fleshed bodies of eleven individuals of varying ages. Segmentation protocol was set, with the exception of each observer selecting their own thresholding value for each scan. The resulting smoothed pelvic surfaces were then compared using deviation analyses. Root mean square error (RMSE), average distance deviation, and maximum deviation distances demonstrated that thresholding values of ∼50 HU (Hounsfield units) are easily tolerated, the surfaces generated are robust to error, and threshold value selection does not systematically vary with user experience. The importance of consistent methodology during segmentation protocol is highlighted here, especially with regards to consistency in both selected thresholding value as well as smoothing protocol, as these variables can affect subsequent measurements of the resultant surfaces. |
doi_str_mv | 10.1016/j.forsciint.2020.110232 |
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As the accessibility and utility of virtual databases of skeletal collections continues to grow, the impact that scan processing procedures has on the accuracy of data obtained from virtual databases remains relatively unknown. This study quantifies the intra- and inter-observer error generated from varying computed tomography (CT) scan processing protocols, including re-segmentation, incrementally varying thresholding value, and data collectors’ selection of the threshold value on a set of virtual subadult pelves. Four observers segmented the subadult ossa coxarum from postmortem CT scans of the fully-fleshed bodies of eleven individuals of varying ages. Segmentation protocol was set, with the exception of each observer selecting their own thresholding value for each scan. The resulting smoothed pelvic surfaces were then compared using deviation analyses. Root mean square error (RMSE), average distance deviation, and maximum deviation distances demonstrated that thresholding values of ∼50 HU (Hounsfield units) are easily tolerated, the surfaces generated are robust to error, and threshold value selection does not systematically vary with user experience. The importance of consistent methodology during segmentation protocol is highlighted here, especially with regards to consistency in both selected thresholding value as well as smoothing protocol, as these variables can affect subsequent measurements of the resultant surfaces.</description><identifier>ISSN: 0379-0738</identifier><identifier>EISSN: 1872-6283</identifier><identifier>DOI: 10.1016/j.forsciint.2020.110232</identifier><identifier>PMID: 32151881</identifier><language>eng</language><publisher>Ireland: Elsevier B.V</publisher><subject>Adolescent ; Amira ; Autopsy ; Biological anthropology ; Bones ; Child ; Child, Preschool ; Computed tomography ; Coxa ; Data collection ; Deviation ; Error analysis ; Female ; Forensic Anthropology ; Forensic osteology ; Forensic sciences ; Geomagic ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Infant ; Male ; Medical imaging ; Medical research ; Observer Variation ; Pelvic Bones - diagnostic imaging ; Precision ; Root-mean-square errors ; Segmentation ; Software ; Subadult ; Tomography, X-Ray Computed ; Virtual anthropology</subject><ispartof>Forensic science international, 2020-04, Vol.309, p.110232-110232, Article 110232</ispartof><rights>2020 Elsevier B.V.</rights><rights>Copyright © 2020 Elsevier B.V. All rights reserved.</rights><rights>2020. Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-67de0988191de1844a776df8d34661188d42d29fc95224afc90f8b64d683416a3</citedby><cites>FETCH-LOGICAL-c399t-67de0988191de1844a776df8d34661188d42d29fc95224afc90f8b64d683416a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2417039204?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32151881$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Stock, Michala K.</creatorcontrib><creatorcontrib>Garvin, Heather M.</creatorcontrib><creatorcontrib>Corron, Louise K.</creatorcontrib><creatorcontrib>Hulse, Cortney N.</creatorcontrib><creatorcontrib>Cirillo, Laura E.</creatorcontrib><creatorcontrib>Klales, Alexandra R.</creatorcontrib><creatorcontrib>Colman, Kerri L.</creatorcontrib><creatorcontrib>Stull, Kyra E.</creatorcontrib><title>The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa</title><title>Forensic science international</title><addtitle>Forensic Sci Int</addtitle><description>•CT scan processing protocols should remain consistent for accurate results.•Slight variation (e.g., ∼50 HU) in thresholding does not substantially alter resultant surfaces.•Error generated by scan processing is less than allowable measurement error (1–2mm).
As the accessibility and utility of virtual databases of skeletal collections continues to grow, the impact that scan processing procedures has on the accuracy of data obtained from virtual databases remains relatively unknown. This study quantifies the intra- and inter-observer error generated from varying computed tomography (CT) scan processing protocols, including re-segmentation, incrementally varying thresholding value, and data collectors’ selection of the threshold value on a set of virtual subadult pelves. Four observers segmented the subadult ossa coxarum from postmortem CT scans of the fully-fleshed bodies of eleven individuals of varying ages. Segmentation protocol was set, with the exception of each observer selecting their own thresholding value for each scan. The resulting smoothed pelvic surfaces were then compared using deviation analyses. Root mean square error (RMSE), average distance deviation, and maximum deviation distances demonstrated that thresholding values of ∼50 HU (Hounsfield units) are easily tolerated, the surfaces generated are robust to error, and threshold value selection does not systematically vary with user experience. The importance of consistent methodology during segmentation protocol is highlighted here, especially with regards to consistency in both selected thresholding value as well as smoothing protocol, as these variables can affect subsequent measurements of the resultant surfaces.</description><subject>Adolescent</subject><subject>Amira</subject><subject>Autopsy</subject><subject>Biological anthropology</subject><subject>Bones</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Computed tomography</subject><subject>Coxa</subject><subject>Data collection</subject><subject>Deviation</subject><subject>Error analysis</subject><subject>Female</subject><subject>Forensic Anthropology</subject><subject>Forensic osteology</subject><subject>Forensic sciences</subject><subject>Geomagic</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Imaging, Three-Dimensional</subject><subject>Infant</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Medical research</subject><subject>Observer Variation</subject><subject>Pelvic Bones - diagnostic imaging</subject><subject>Precision</subject><subject>Root-mean-square errors</subject><subject>Segmentation</subject><subject>Software</subject><subject>Subadult</subject><subject>Tomography, X-Ray Computed</subject><subject>Virtual anthropology</subject><issn>0379-0738</issn><issn>1872-6283</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFUcuOEzEQtBCIDQu_AJa4cJngx8Tj4RZFvKSVuISz5bV7Ng4zdrA9q-Uv-GQ6O8seuHDqVru6qstFyBvO1pxx9f64HlIuLoRY14IJnHImpHhCVlx3olFCy6dkxWTXN6yT-oK8KOXIGNtshHpOLqTgG641X5Hf-wPQMJ1SrjY6oGmgp5wclBLizdL6OUOhNnpaD9gd0ujprR1nHIZId3tanI20wM0EsdoaUjyzlB8wQrUjxXJ-KB_oNlK4s9NpBDrf09d77clWVKCpUJfu7EvybLBjgVcP9ZJ8__Rxv_vSXH37_HW3vWqc7PvaqM4D69FCzz1w3ba265QftJetUhy9-VZ40Q-u3wjRWqxs0Neq9UrLlisrL8m7hRc9_kQv1UyhOBhHGyHNxQjZbTQuqx6hb_-BHtOcI15nRMs7JnvBWkR1C8rlVEqGwZxymGz-ZTgz59DM0TyGZs6hmSU03Hz9wD9fT-Af9_6mhIDtAgD8kNsA2SALYFw-ZHDV-BT-K_IHeuitoQ</recordid><startdate>202004</startdate><enddate>202004</enddate><creator>Stock, Michala K.</creator><creator>Garvin, Heather M.</creator><creator>Corron, Louise K.</creator><creator>Hulse, Cortney N.</creator><creator>Cirillo, Laura E.</creator><creator>Klales, Alexandra R.</creator><creator>Colman, Kerri L.</creator><creator>Stull, Kyra E.</creator><general>Elsevier B.V</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>202004</creationdate><title>The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa</title><author>Stock, Michala K. ; Garvin, Heather M. ; Corron, Louise K. ; Hulse, Cortney N. ; Cirillo, Laura E. ; Klales, Alexandra R. ; Colman, Kerri L. ; Stull, Kyra E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-67de0988191de1844a776df8d34661188d42d29fc95224afc90f8b64d683416a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adolescent</topic><topic>Amira</topic><topic>Autopsy</topic><topic>Biological anthropology</topic><topic>Bones</topic><topic>Child</topic><topic>Child, Preschool</topic><topic>Computed tomography</topic><topic>Coxa</topic><topic>Data collection</topic><topic>Deviation</topic><topic>Error analysis</topic><topic>Female</topic><topic>Forensic Anthropology</topic><topic>Forensic osteology</topic><topic>Forensic sciences</topic><topic>Geomagic</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Imaging, Three-Dimensional</topic><topic>Infant</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Medical research</topic><topic>Observer Variation</topic><topic>Pelvic Bones - diagnostic imaging</topic><topic>Precision</topic><topic>Root-mean-square errors</topic><topic>Segmentation</topic><topic>Software</topic><topic>Subadult</topic><topic>Tomography, X-Ray Computed</topic><topic>Virtual anthropology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Stock, Michala K.</creatorcontrib><creatorcontrib>Garvin, Heather M.</creatorcontrib><creatorcontrib>Corron, Louise K.</creatorcontrib><creatorcontrib>Hulse, Cortney N.</creatorcontrib><creatorcontrib>Cirillo, Laura E.</creatorcontrib><creatorcontrib>Klales, Alexandra R.</creatorcontrib><creatorcontrib>Colman, Kerri L.</creatorcontrib><creatorcontrib>Stull, Kyra E.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Forensic science international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Stock, Michala K.</au><au>Garvin, Heather M.</au><au>Corron, Louise K.</au><au>Hulse, Cortney N.</au><au>Cirillo, Laura E.</au><au>Klales, Alexandra R.</au><au>Colman, Kerri L.</au><au>Stull, Kyra E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa</atitle><jtitle>Forensic science international</jtitle><addtitle>Forensic Sci Int</addtitle><date>2020-04</date><risdate>2020</risdate><volume>309</volume><spage>110232</spage><epage>110232</epage><pages>110232-110232</pages><artnum>110232</artnum><issn>0379-0738</issn><eissn>1872-6283</eissn><abstract>•CT scan processing protocols should remain consistent for accurate results.•Slight variation (e.g., ∼50 HU) in thresholding does not substantially alter resultant surfaces.•Error generated by scan processing is less than allowable measurement error (1–2mm).
As the accessibility and utility of virtual databases of skeletal collections continues to grow, the impact that scan processing procedures has on the accuracy of data obtained from virtual databases remains relatively unknown. This study quantifies the intra- and inter-observer error generated from varying computed tomography (CT) scan processing protocols, including re-segmentation, incrementally varying thresholding value, and data collectors’ selection of the threshold value on a set of virtual subadult pelves. Four observers segmented the subadult ossa coxarum from postmortem CT scans of the fully-fleshed bodies of eleven individuals of varying ages. Segmentation protocol was set, with the exception of each observer selecting their own thresholding value for each scan. The resulting smoothed pelvic surfaces were then compared using deviation analyses. Root mean square error (RMSE), average distance deviation, and maximum deviation distances demonstrated that thresholding values of ∼50 HU (Hounsfield units) are easily tolerated, the surfaces generated are robust to error, and threshold value selection does not systematically vary with user experience. The importance of consistent methodology during segmentation protocol is highlighted here, especially with regards to consistency in both selected thresholding value as well as smoothing protocol, as these variables can affect subsequent measurements of the resultant surfaces.</abstract><cop>Ireland</cop><pub>Elsevier B.V</pub><pmid>32151881</pmid><doi>10.1016/j.forsciint.2020.110232</doi><tpages>1</tpages></addata></record> |
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subjects | Adolescent Amira Autopsy Biological anthropology Bones Child Child, Preschool Computed tomography Coxa Data collection Deviation Error analysis Female Forensic Anthropology Forensic osteology Forensic sciences Geomagic Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Infant Male Medical imaging Medical research Observer Variation Pelvic Bones - diagnostic imaging Precision Root-mean-square errors Segmentation Software Subadult Tomography, X-Ray Computed Virtual anthropology |
title | The importance of processing procedures and threshold values in CT scan segmentation of skeletal elements: An example using the immature os coxa |
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