title: Three-dimensional texture analysis of cancellous bone cores evaluated at clinical CT resolutions.
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.
authors.affiliation: Department of Electrical & Computer Engineering, The Ohio State University, Columbus, OH 43210, USA.
authors.forename: Chad
authors.initials: C
authors.lastname: Showalter
authors.forename: Bradley D
authors.initials: BD
authors.lastname: Clymer
authors.forename: Bradford
authors.initials: B
authors.lastname: Richmond
authors.forename: Kimerly
authors.initials: K
authors.lastname: Powell
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002102:Cadaver; D002111:Calcaneus / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D015233:Models, Statistical; D012044:Regression Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods*