Automated, Foot-Bone Registration Using Subdivision-Embedded Atlases for Spatial Mapping of Bone Mineral Density
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We present an atlas-based registration method for bones segmented from quantitative computed tomography (QCT) scans, with the goal of mapping their interior bone mineral densities (BMDs) volumetrically. We introduce a new type of deformable atlas, called subdivision-embedded atlas, which consists of a control grid represented as a tetrahedral subdivision mesh and a template bone surface embedded within the grid. Compared to a typical lattice-based deformation grid, the subdivision control grid possesses a relatively small degree of freedom tailored to the shape of the bone, which allows efficient fitting onto subjects. Compared with previous subdivision atlases, the novelty of our atlas lies in the addition of the embedded template surface, which further increases the accuracy of the fitting. Using this new atlas representation, we developed an efficient and fully automated pipeline for registering atlases of 12 tarsal and metatarsal bones to a segmented QCT scan of a human foot. Our evaluation shows that the mapping of BMD enabled by the registration is consistent for bones in repeated scans, and the regional BMD automatically computed from the mapping is not significantly different from expert annotations. The results suggest that our improved subdivision-based registration method is a reliable, efficient way to replace manual labor for measuring regional BMD in foot bones in QCT scans.
KeywordsBone mineral density Registration Atlas Subdivision
This work is supported in part by NIH grants (R21DK79457 and R21NS058553) and NSF grants (DBI-0743691 and CCF-0702662).
- 4.Liu L, Raber D, Nopachai D, Commean P, Sinacore D, Prior F, Pless R, Ju T: Interactive separation of segmented bones in ct volumes using graph cut. In: Proc. of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I. 2008, 296–304Google Scholar
- 6.Toga A: Brain Warping. Academic, 1998Google Scholar
- 17.MacCracken R, Joy K: Free-form deformations with lattices of arbitrary topology. In: Proc. of the 23rd annual conference on computer graphics and interactive techniques. SIGGRAPH ′96: 1996, 181–188Google Scholar
- 20.Warren J, Weimer H: Subdivision methods for geometric design. Morgan-Kaufmann, 2002Google Scholar
- 21.Schaefer S, Hakenberg J, Warren J: Smooth subdivision of tetrahedral meshes. In: Proc. the Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, Eurographics Association. 2004, 151–158Google Scholar
- 24.Taubin G: A signal processing approach to fair surface design. In: SIGGRAPH ′95: Proc. of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, New York, NY, USA, ACM. 1995, 351–358Google Scholar
- 25.Garland M, Heckbert P: Surface simplification using quadric error metrics. In: Proc. of the 24th Annual Conference on Computer Graphics and Interactive Techniques. SIGGRAPH ′97. 1997, 209–216Google Scholar
- 27.Smith KE, Whiting BR, Reiker GG, Commean PK, Sinacore DR, Prior FW: Assessment of technical and biological parameters of volumetric quantitative computed tomography in the foot: a phantom study. Osteoporosis International, In Press, 2012Google Scholar
- 28.Robb RA: Three Dimensional Biomedical Imaging: Principles and Practice. VCH, New York, 1995Google Scholar
- 29.Robb RA, Hanson DP, Karwoski RA, Larson AG, Workman EL, Stacy MC. Analyze: a comprehensive, operator-interactive software.Google Scholar
- 30.Russ JC: The Image Processing Handbook, 2nd edition. CRC, Boca Raton, FL, 1995Google Scholar
- 31.Rasband WS: ImageJ. In: National Institutes of Health; http://rsbweb.nih.gov/ij/. 1997.
- 32.Chintalapani G, Ellingsen L, Sadowsky O, Prince J, Taylor R: Statistical atlases of bone anatomy: construction, iterative improvement and validation. In Proc. MICCAI′07. 2007, 499–506Google Scholar