Abstract
We present a novel approach to statistically characterize histograms of model-relative image regions. A multiscale model is used as an aperture to define image regions at multiple scales. We use this image description to define an appearance model for deformable model segmentation. Appearance models measure the likelihood of an object given a target image. To determine this likelihood we compute pixel intensity histograms of local model-relative image regions from a 3D image volume near the object boundary. We use a Gaussian model to statistically characterize the variation of non-parametric histograms mapped to Euclidean space using the Earth Mover’s distance.
The new method is illustrated and evaluated in a deformable model segmentation study on CT images of the human bladder, prostate, and rectum. Results show improvement over a previous profile based appearance model, out-performance of statistically modeled histograms over simple histogram measurements, and advantages of regional histograms at a fixed local scale over a fixed global scale.
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References
Broadhurst, R.E.: Simplifying texture classification. Technical report, University of North Carolina (2004), http://midag.cs.unc.edu
Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Image Processing 10, 266–277 (2001)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, p. 484. Springer, Heidelberg (1998)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models – their training and application. In: Computer Vision and Image Understanding, vol. 61, pp. 38–59 (1995)
Freedman, D., Radke, R.J., Zhang, T., Jeong, Y., Lovelock, D.M., Chen, G.T.Y.: Model-based segmentation of medical imagery by matching distributions. IEEE Trans. on Medical Imaging 24, 281–292 (2005)
Joshi, S.: Large Deformation Diffeomorphisms and Gaussian Random Fields for Statistical Characterization of Brain Submanifolds. PhD thesis (1997)
Levina, E.: Statistical Issues in Texture Analysis. PhD thesis (2002)
Levina, E., Bickel, P.: The earth mover’s distance is the mallows distance: Some insights from statistics. In: ICCV, pp. 251–256 (2001)
Pizer, S.M., Fletcher, P.T., Joshi, S., Gash, A.G., Stough, J., Thall, A., Tracton, G., Chaney, E.L.: A method & software for segmentation of anatomic object ensembles by deformable m-reps. Medical Physics (to appear)
Pizer, S.M., Fletcher, T., Fridman, Y., Fritsch, D.S., Gash, A.G., Glotzer, J.M., Joshi, S., Thall, A., Tracton, G., Yushkevich, P., Chaney, E.L.: Deformable m-reps for 3d medical image segmentation. In: IJCV, vol. 55(2), pp. 85–106 (2003)
Pizer, S.M., Jeong, J.Y., Broadhurst, R.E., Ho, S., Stough, J.: Deep structure of images in populations via geometric models in populations. In: Fogh Olsen, O., Florack, L.M.J., Kuijper, A. (eds.) DSSCV 2005. LNCS, vol. 3753, pp. 49–59. Springer, Heidelberg (2005)
Pizer, S.M., Jeong, J.-Y., Lu, C., Muller, K., Joshi, S.: Estimating the statistics of multi-object anatomic geometry using inter-object relationships. In: Fogh Olsen, O., Florack, L.M.J., Kuijper, A. (eds.) DSSCV 2005. LNCS, vol. 3753, pp. 60–71. Springer, Heidelberg (2005)
Rubner, Y., Tomasi, C., Guibas, L.J.: A metric for distributions with applications to image databases. In: ICCV, pp. 59–66 (1998)
Scott, I.M., Cootes, T.F., Taylor, C.J.: Improving appearance model matching using local image structure. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 258–269. Springer, Heidelberg (2003)
Stough, J., Pizer, S.M., Chaney, E.L., Rao, M.: Clustering on image boundary regions for deformable model segmentation. In: ISBI, April 2004, pp. 436–439 (2004)
Tsai, A., Yezzi, A., Wells, W., Tempany, C., Tucker, D., Fan, A., Grimson, W.E., Willsky, A.: A shape-based approach to the segmentation of medical imagery using level sets. IEEE Trans. Medical Imaging 22 (February 2003)
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Broadhurst, R.E., Stough, J., Pizer, S.M., Chaney, E.L. (2005). Histogram Statistics of Local Model-Relative Image Regions. In: Fogh Olsen, O., Florack, L., Kuijper, A. (eds) Deep Structure, Singularities, and Computer Vision. DSSCV 2005. Lecture Notes in Computer Science, vol 3753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577812_7
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DOI: https://doi.org/10.1007/11577812_7
Publisher Name: Springer, Berlin, Heidelberg
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