Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions
The objective of this study was to determine if three-dimensional (3D) Haralick co-occurrence texture measures calculated from low-resolution CT images of trabecular bone correlate with 3D structural indices measured from high-resolution CT images. Thirty-three cubical regions of trabecular bone fro...
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| Veröffentlicht in: | Osteoporosis international 2006-02, Vol.17 (2), p.259-266 |
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| creator | SHOWALTER, Chad CLYMER, Bradley D RICHMOND, Bradford POWELL, Kimerly |
| description | The objective of this study was to determine if three-dimensional (3D) Haralick co-occurrence texture measures calculated from low-resolution CT images of trabecular bone correlate with 3D structural indices measured from high-resolution CT images. Thirty-three cubical regions of trabecular bone from human calcanei were analyzed using images obtained from a micro-computed tomography (micro-CT) scanner. 3D measures of bone architecture were calculated. The original images were then subsampled by factors of 5, 10, 15, and 20, and 3D texture features were calculated for each set of subsampled images. Linear regression models showed that co-occurrence texture features were significantly correlated with structural indices. Over 90% of the variation in three different structural indices was explained in two-variable regression models using texture features as predictors when the voxel side length was reduced by a factor of 10. Texture features calculated from clinical images may increase our ability to obtain trabecular bone architectural information when high-resolution images are unobtainable. |
| doi_str_mv | 10.1007/s00198-005-1994-1 |
| format | Article |
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Thirty-three cubical regions of trabecular bone from human calcanei were analyzed using images obtained from a micro-computed tomography (micro-CT) scanner. 3D measures of bone architecture were calculated. The original images were then subsampled by factors of 5, 10, 15, and 20, and 3D texture features were calculated for each set of subsampled images. Linear regression models showed that co-occurrence texture features were significantly correlated with structural indices. Over 90% of the variation in three different structural indices was explained in two-variable regression models using texture features as predictors when the voxel side length was reduced by a factor of 10. Texture features calculated from clinical images may increase our ability to obtain trabecular bone architectural information when high-resolution images are unobtainable.</description><identifier>ISSN: 0937-941X</identifier><identifier>EISSN: 1433-2965</identifier><identifier>DOI: 10.1007/s00198-005-1994-1</identifier><identifier>PMID: 16170445</identifier><language>eng</language><publisher>London: Springer</publisher><subject>Aged ; Aged, 80 and over ; Architecture ; Biological and medical sciences ; Biomedical engineering ; Bone density ; Cadaver ; Calcaneus - diagnostic imaging ; Computer engineering ; Diseases of the osteoarticular system ; Female ; Humans ; Image Processing, Computer-Assisted - methods ; Imaging, Three-Dimensional - methods ; Medical imaging ; Medical sciences ; Models, Statistical ; Osteoporosis ; Osteoporosis. Osteomalacia. Paget disease ; Regression Analysis ; Scanners ; Three dimensional imaging ; Tomography ; Tomography, X-Ray Computed - methods</subject><ispartof>Osteoporosis international, 2006-02, Vol.17 (2), p.259-266</ispartof><rights>2006 INIST-CNRS</rights><rights>International Osteoporosis Foundation and National Osteoporosis Foundation 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-24180d7b1c2360702045ee7828d7f50c949c2dc69b2a320f06b4b6290bfdf21b3</citedby><cites>FETCH-LOGICAL-c356t-24180d7b1c2360702045ee7828d7f50c949c2dc69b2a320f06b4b6290bfdf21b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17453308$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16170445$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>SHOWALTER, Chad</creatorcontrib><creatorcontrib>CLYMER, Bradley D</creatorcontrib><creatorcontrib>RICHMOND, Bradford</creatorcontrib><creatorcontrib>POWELL, Kimerly</creatorcontrib><title>Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions</title><title>Osteoporosis international</title><addtitle>Osteoporos Int</addtitle><description>The objective of this study was to determine if three-dimensional (3D) Haralick co-occurrence texture measures calculated from low-resolution CT images of trabecular bone correlate with 3D structural indices measured from high-resolution CT images. Thirty-three cubical regions of trabecular bone from human calcanei were analyzed using images obtained from a micro-computed tomography (micro-CT) scanner. 3D measures of bone architecture were calculated. The original images were then subsampled by factors of 5, 10, 15, and 20, and 3D texture features were calculated for each set of subsampled images. Linear regression models showed that co-occurrence texture features were significantly correlated with structural indices. Over 90% of the variation in three different structural indices was explained in two-variable regression models using texture features as predictors when the voxel side length was reduced by a factor of 10. Texture features calculated from clinical images may increase our ability to obtain trabecular bone architectural information when high-resolution images are unobtainable.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Architecture</subject><subject>Biological and medical sciences</subject><subject>Biomedical engineering</subject><subject>Bone density</subject><subject>Cadaver</subject><subject>Calcaneus - diagnostic imaging</subject><subject>Computer engineering</subject><subject>Diseases of the osteoarticular system</subject><subject>Female</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>Medical imaging</subject><subject>Medical sciences</subject><subject>Models, Statistical</subject><subject>Osteoporosis</subject><subject>Osteoporosis. Osteomalacia. Paget disease</subject><subject>Regression Analysis</subject><subject>Scanners</subject><subject>Three dimensional imaging</subject><subject>Tomography</subject><subject>Tomography, X-Ray Computed - methods</subject><issn>0937-941X</issn><issn>1433-2965</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpdkE1r3DAQhkVpabZpf0AuRQTam9oZSZasY1jSD1joZQu9qbI8Jg5eK5Xskvz7atmFQE-DmOd9GT2MXSF8QgD7uQCgawVAI9A5LfAF26BWSkhnmpdsA05Z4TT-umBvSrmHmnHOvmYXaNCC1s2G_d7fZSLRjweay5jmMPGFHpc1Ew_18VTGwtPAY5gjTVNaC-_STDymTIXT3zCtYaGeh4XHaZzHWPPbPa_LNK1L7Stv2ashTIXenecl-_nldr_9JnY_vn7f3uxEVI1ZhNTYQm87jFIZsCBBN0S2lW1vhwai0y7KPhrXyaAkDGA63RnpoBv6QWKnLtnHU-9DTn9WKos_jOV4c5ipnu2NNeCslBW8_g-8T2uufy1eYtuiaSVWCE9QzKmUTIN_yOMh5CeP4I_u_cm9r-790b0_Zt6fi9fuQP1z4iy7Ah_OQChV1JCr1LE8c7YyClr1D-QqjBo</recordid><startdate>20060201</startdate><enddate>20060201</enddate><creator>SHOWALTER, Chad</creator><creator>CLYMER, Bradley D</creator><creator>RICHMOND, Bradford</creator><creator>POWELL, Kimerly</creator><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><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>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope></search><sort><creationdate>20060201</creationdate><title>Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions</title><author>SHOWALTER, Chad ; CLYMER, Bradley D ; RICHMOND, Bradford ; POWELL, Kimerly</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-24180d7b1c2360702045ee7828d7f50c949c2dc69b2a320f06b4b6290bfdf21b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Architecture</topic><topic>Biological and medical sciences</topic><topic>Biomedical engineering</topic><topic>Bone density</topic><topic>Cadaver</topic><topic>Calcaneus - diagnostic imaging</topic><topic>Computer engineering</topic><topic>Diseases of the osteoarticular system</topic><topic>Female</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>Medical imaging</topic><topic>Medical sciences</topic><topic>Models, Statistical</topic><topic>Osteoporosis</topic><topic>Osteoporosis. Osteomalacia. Paget disease</topic><topic>Regression Analysis</topic><topic>Scanners</topic><topic>Three dimensional imaging</topic><topic>Tomography</topic><topic>Tomography, X-Ray Computed - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>SHOWALTER, Chad</creatorcontrib><creatorcontrib>CLYMER, Bradley D</creatorcontrib><creatorcontrib>RICHMOND, Bradford</creatorcontrib><creatorcontrib>POWELL, Kimerly</creatorcontrib><collection>Pascal-Francis</collection><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>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</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>MEDLINE - Academic</collection><jtitle>Osteoporosis international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>SHOWALTER, Chad</au><au>CLYMER, Bradley D</au><au>RICHMOND, Bradford</au><au>POWELL, Kimerly</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions</atitle><jtitle>Osteoporosis international</jtitle><addtitle>Osteoporos Int</addtitle><date>2006-02-01</date><risdate>2006</risdate><volume>17</volume><issue>2</issue><spage>259</spage><epage>266</epage><pages>259-266</pages><issn>0937-941X</issn><eissn>1433-2965</eissn><abstract>The objective of this study was to determine if three-dimensional (3D) Haralick co-occurrence texture measures calculated from low-resolution CT images of trabecular bone correlate with 3D structural indices measured from high-resolution CT images. Thirty-three cubical regions of trabecular bone from human calcanei were analyzed using images obtained from a micro-computed tomography (micro-CT) scanner. 3D measures of bone architecture were calculated. The original images were then subsampled by factors of 5, 10, 15, and 20, and 3D texture features were calculated for each set of subsampled images. Linear regression models showed that co-occurrence texture features were significantly correlated with structural indices. Over 90% of the variation in three different structural indices was explained in two-variable regression models using texture features as predictors when the voxel side length was reduced by a factor of 10. Texture features calculated from clinical images may increase our ability to obtain trabecular bone architectural information when high-resolution images are unobtainable.</abstract><cop>London</cop><pub>Springer</pub><pmid>16170445</pmid><doi>10.1007/s00198-005-1994-1</doi><tpages>8</tpages></addata></record> |
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| subjects | Aged Aged, 80 and over Architecture Biological and medical sciences Biomedical engineering Bone density Cadaver Calcaneus - diagnostic imaging Computer engineering Diseases of the osteoarticular system Female Humans Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods Medical imaging Medical sciences Models, Statistical Osteoporosis Osteoporosis. Osteomalacia. Paget disease Regression Analysis Scanners Three dimensional imaging Tomography Tomography, X-Ray Computed - methods |
| title | Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions |
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