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Automated detection of patient movement during a CBCT scan based on the projection data
Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow the...
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Published in: | Oral surgery, oral medicine, oral pathology and oral radiology oral medicine, oral pathology and oral radiology, 2015-04, Vol.119 (4), p.468-472 |
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container_title | Oral surgery, oral medicine, oral pathology and oral radiology |
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creator | Schulze, Ralf K.W., Prof Dr med dent Michel, Michel, Dr med dent Schwanecke, Ulrich, Prof Dr rer nat |
description | Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evaluated with the software. Results 10 out of 79 (13%) were allocated to a patient movement. A threshold of 0.4 pixel/frame transition was empirically determined as indicating motion by visual assessment of the image sequence. Relative to this standard of reference, the software reached 80% sensitivity versus 67% specificity. Conclusions Optical flow seems to be an efficient concept for automated detection of patient motion on the projection images acquired during a CBCT scan. |
doi_str_mv | 10.1016/j.oooo.2014.12.008 |
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Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evaluated with the software. Results 10 out of 79 (13%) were allocated to a patient movement. A threshold of 0.4 pixel/frame transition was empirically determined as indicating motion by visual assessment of the image sequence. Relative to this standard of reference, the software reached 80% sensitivity versus 67% specificity. Conclusions Optical flow seems to be an efficient concept for automated detection of patient motion on the projection images acquired during a CBCT scan.</description><identifier>ISSN: 2212-4403</identifier><identifier>EISSN: 2212-4411</identifier><identifier>DOI: 10.1016/j.oooo.2014.12.008</identifier><identifier>PMID: 25660275</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Algorithms ; Cone-Beam Computed Tomography ; Dentistry ; Feasibility Studies ; Humans ; Imaging, Three-Dimensional ; Movement ; Phantoms, Imaging ; Radiographic Image Interpretation, Computer-Assisted ; Sensitivity and Specificity ; Software ; Surgery</subject><ispartof>Oral surgery, oral medicine, oral pathology and oral radiology, 2015-04, Vol.119 (4), p.468-472</ispartof><rights>Elsevier Inc.</rights><rights>2015 Elsevier Inc.</rights><rights>Copyright © 2015 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-fa2e31661cb1184aa1b0fe9f73a6aa80885fdcc4a9125efd6d3d0e3908bb0fa73</citedby><cites>FETCH-LOGICAL-c411t-fa2e31661cb1184aa1b0fe9f73a6aa80885fdcc4a9125efd6d3d0e3908bb0fa73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25660275$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Schulze, Ralf K.W., Prof Dr med dent</creatorcontrib><creatorcontrib>Michel, Michel, Dr med dent</creatorcontrib><creatorcontrib>Schwanecke, Ulrich, Prof Dr rer nat</creatorcontrib><title>Automated detection of patient movement during a CBCT scan based on the projection data</title><title>Oral surgery, oral medicine, oral pathology and oral radiology</title><addtitle>Oral Surg Oral Med Oral Pathol Oral Radiol</addtitle><description>Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evaluated with the software. Results 10 out of 79 (13%) were allocated to a patient movement. A threshold of 0.4 pixel/frame transition was empirically determined as indicating motion by visual assessment of the image sequence. Relative to this standard of reference, the software reached 80% sensitivity versus 67% specificity. Conclusions Optical flow seems to be an efficient concept for automated detection of patient motion on the projection images acquired during a CBCT scan.</description><subject>Algorithms</subject><subject>Cone-Beam Computed Tomography</subject><subject>Dentistry</subject><subject>Feasibility Studies</subject><subject>Humans</subject><subject>Imaging, Three-Dimensional</subject><subject>Movement</subject><subject>Phantoms, Imaging</subject><subject>Radiographic Image Interpretation, Computer-Assisted</subject><subject>Sensitivity and Specificity</subject><subject>Software</subject><subject>Surgery</subject><issn>2212-4403</issn><issn>2212-4411</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp9kcFu1DAQhiMEolXpC3BAPnLZ4LGz3qyEkMqqQKVKPdCqR2tiT8AhiZfYqdS3Z6JdeuihvtiH__ttf1MU70GWIMF86srIq1QSqhJUKWX9qjhVCtSqqgBeP52lPinOU-okL8Ngpd4WJ2ptjFSb9WlxfzHnOGAmLzxlcjnEUcRW7DEHGrMY4gMNy8HPUxh_CRS7r7tbkRyOosHEGOfzbxL7KXZH3GPGd8WbFvtE58f9rLj7dnm7-7G6vvl-tbu4Xjl-ZV61qEiDMeAagLpChEa2tG03Gg1iLet63XrnKtyCWlPrjddekt7KuuEgbvRZ8fHQy_f_nSllO4TkqO9xpDgny93K6E1tDEfVIeqmmNJErd1PYcDp0YK0i1Pb2cWpXZxaUJadMvTh2D83A_kn5L9BDnw-BIh_-RBossmxOUc-TOzD-hhe7v_yDHd9GIPD_g89UuriPI3sz4JNDNify1SXoULFJaBr_Q8OjJy0</recordid><startdate>20150401</startdate><enddate>20150401</enddate><creator>Schulze, Ralf K.W., Prof Dr med dent</creator><creator>Michel, Michel, Dr med dent</creator><creator>Schwanecke, Ulrich, Prof Dr rer nat</creator><general>Elsevier Inc</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>7X8</scope></search><sort><creationdate>20150401</creationdate><title>Automated detection of patient movement during a CBCT scan based on the projection data</title><author>Schulze, Ralf K.W., Prof Dr med dent ; Michel, Michel, Dr med dent ; Schwanecke, Ulrich, Prof Dr rer nat</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-fa2e31661cb1184aa1b0fe9f73a6aa80885fdcc4a9125efd6d3d0e3908bb0fa73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Cone-Beam Computed Tomography</topic><topic>Dentistry</topic><topic>Feasibility Studies</topic><topic>Humans</topic><topic>Imaging, Three-Dimensional</topic><topic>Movement</topic><topic>Phantoms, Imaging</topic><topic>Radiographic Image Interpretation, Computer-Assisted</topic><topic>Sensitivity and Specificity</topic><topic>Software</topic><topic>Surgery</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schulze, Ralf K.W., Prof Dr med dent</creatorcontrib><creatorcontrib>Michel, Michel, Dr med dent</creatorcontrib><creatorcontrib>Schwanecke, Ulrich, Prof Dr rer nat</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Oral surgery, oral medicine, oral pathology and oral radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schulze, Ralf K.W., Prof Dr med dent</au><au>Michel, Michel, Dr med dent</au><au>Schwanecke, Ulrich, Prof Dr rer nat</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automated detection of patient movement during a CBCT scan based on the projection data</atitle><jtitle>Oral surgery, oral medicine, oral pathology and oral radiology</jtitle><addtitle>Oral Surg Oral Med Oral Pathol Oral Radiol</addtitle><date>2015-04-01</date><risdate>2015</risdate><volume>119</volume><issue>4</issue><spage>468</spage><epage>472</epage><pages>468-472</pages><issn>2212-4403</issn><eissn>2212-4411</eissn><abstract>Objectives To develop an automated procedure to detect patient motion on the projection images acquired during a cone beam computed tomography (CBCT) scan and to evaluate the method's feasibility on small real-world CBCT images in relation to visual assessment. Methods Based on optical flow theory, software was developed using the sequence of the projection images of a CBCT machine for automated detection of patient motion. Averaged acceleration vectors were used as measurement data and compared with visual assessment of the projection images displayed as video. Seventy-nine CBCT data sets (small field-of-view: 40 mm) from our patient database were selected in a sequential fashion and evaluated with the software. Results 10 out of 79 (13%) were allocated to a patient movement. A threshold of 0.4 pixel/frame transition was empirically determined as indicating motion by visual assessment of the image sequence. Relative to this standard of reference, the software reached 80% sensitivity versus 67% specificity. Conclusions Optical flow seems to be an efficient concept for automated detection of patient motion on the projection images acquired during a CBCT scan.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>25660275</pmid><doi>10.1016/j.oooo.2014.12.008</doi><tpages>5</tpages></addata></record> |
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subjects | Algorithms Cone-Beam Computed Tomography Dentistry Feasibility Studies Humans Imaging, Three-Dimensional Movement Phantoms, Imaging Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Software Surgery |
title | Automated detection of patient movement during a CBCT scan based on the projection data |
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