Proceedings ArticleDOI
Detection of osteoporosis by morphological granulometries
Edward R. Dougherty,Yi Chen,Saara M D Totterman,Joseph P. Hornak +3 more
- Vol. 1660, pp 666-680
TLDR
A gray-scale version of the methodology to detect osteoporosis in magnetic resonance (MR) images of the wrist is applied, using maximum-likelihood classification to apply the local-pattern-spectra moment information.Abstract:
Local morphological granulometries are generated by opening an image successively by an increasing family of structuring elements and, at each pixel, keeping an image area count in a fixed-size window about the pixel. After normalization there is at each pixel a probability density, called a `local pattern spectrum,' and the moments of this density are used to classify the pixel according to surrounding texture. The method having been developed for binary images, the present paper applies a gray-scale version of the methodology to detect osteoporosis in magnetic resonance (MR) images of the wrist. Maximum-likelihood classification is used to apply the local-pattern-spectra moment information. Owing to the presence of a continuous intertwined network of bone fibers called trabeculae, when imaged by an MR imaging system a normal region of bone tissue possesses a coarse, grainy texture resulting in characteristic granulometric features. Osteoporosis is a metabolic bone disease typified by a gradual loss of trabecular bone, and this loss is revealed by significant changes in the granulometric features, thereby leading to detection.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.read more
Citations
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Off-line signature verification by local granulometric size distributions
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Estimation of optimal morphological t-opening parameters based on independent observation of signal and noise pattern spectra
Edward R. Dougherty,Robert M. Haralick,Yi Chen,Carsten Agerskov,Ulrik Jacobi,Poul Henrik Sloth +5 more
TL;DR: An optimization procedure based upon the individual pattern spectra of the signal and noise, where if the image and noise grains are disjoint, then the pattern-spectra parametric estimation procedure yields exactly the optimal value of the parameter.
Gray-scale granulometries compatible with spatial scalings
TL;DR: In this paper, a general extension of binary Euclidean granulometries to gray-scale images using the notion of a spatial scaling (as opposed to umbral scaling) is described.
Journal ArticleDOI
Gray-scale granulometries compatible with spatial scalings
TL;DR: In this paper, a general extension of binary Euclidean granulometries to gray-scale images using the notion of a spatial scaling (as opposed to umbral scaling) is described.
References
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Journal ArticleDOI
Morphological texture-based maximum-likelihood pixel classification based on local granulometric moments
TL;DR: A detailed analysis of this pixel classification methodology using a Gaussian maximum likelihood classifier is provided, and included is a statistical study of classification accuracy, feature optimization, and robustness with respect to various relevant noise models.
Journal ArticleDOI
In vivo quantitative characterization of trabecular bone by NMR interferometry and localized proton spectroscopy.
John C. Ford,Felix W. Wehrli +1 more
TL;DR: In trabecular bone the NMR linewidth is found to be governed by the magnetic field inhomogeneity arising from the difference in magnetic permeability between bone and marrow.
Journal ArticleDOI
Morphological image segmentation by local granulometric size distributions
TL;DR: An adaptation of the method that is appropriate to texture-based segmentation is described, and exact and asymptotic characterizations of these distributions are developed for the mean image of a basic convexity model.
Journal ArticleDOI
Trabecular Architecture in Iliac Crest Bone Biopsies: Infra-individual Variability in Structural Parameters and Changes with Age
TL;DR: The view that bone loss with aging occurs primarily through a mechanism involving complete disappearance of individual trabecular plates is supported, using bilateral iliac crest samples obtained at autopsy from subjects who had died suddenly.