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Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements.

Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Research Abstract Details 

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  • Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Abstract Text:

    roland krugRoland Krug,julio carballido-gamioJulio Carballido-Gamio,andrew j burghardtAndrew J Burghardt,sebastian haaseSebastian Haase,john w sedatJohn W Sedat,william c mossWilliam C Moss,sharmila majumdarSharmila Majumdar,

    Trabecular bone structure and bone density contribute to the strength of bone and are important in the study of osteoporosis. Wavelets are a powerful tool in characterizing and quantifying texture in an image. The purpose of this study was to validate wavelets as a tool in computing trabecular bone thickness directly from gray-level images. To this end, eight cylindrical cores of vertebral trabecular bone were imaged using 3-T magnetic resonance imaging (MRI) and micro-computed tomography (microCT). Thickness measurements of the trabecular bone from the wavelet-based analysis were compared with standard 2D structural parameters analogous to bone histomorphometry (MR images) and direct 3D distance transformation methods (microCT images). Additionally, bone volume fraction was determined using each method. The average difference in trabecular thickness between the wavelet and standard methods was less than the size of 1 pixel size for both MRI and microCT analysis. A correlation (R) of .94 for microCT measurements and that of .52 for MRI were found for the bone volume fraction. Based on these results, we conclude that wavelet-based methods deliver results comparable with those from established MR histomorphometric measurements. Because the wavelet transform is more robust with respect to image noise and operates directly on gray-level images, it could be a powerful tool for computing structural bone parameters from MR images acquired using high resolution and thus limited signal scenarios.

    Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Publishing Authors By Initials

    r krugR Krug,j carballido-gamioJ Carballido-Gamio,aj burghardtAJ Burghardt,s haaseS Haase,jw sedatJW Sedat,wc mossWC Moss,s majumdarS Majumdar,

    For similar tomography, x-ray computed research abstracts see: tomography, x-ray computed research

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    Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Journal Published:

    PUBLICATION TYPE: Validation Studies

    Journal: Magnetic resonance imaging

    VOLUME: 25

    Page Numbers: 392-8

    Journal Abbreviation:

    ISSN: 0730-725X

    DAY: 14

    MONTH: 11

    YEAR: 2006

    Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Information

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    LANGUAGE: eng

    NlmUniqueID: 8214883

    Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Keywords Mesh Terms:

    KEYWORDS: Tomography, X-Ray Computed

    MESH TERMS: physiology

    Chemical & Substance for Abstract: Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements. Information

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    Grant and Affiliation Information for Wavelet-based characterization of vertebral trabecular bone structure from magnetic resonance images at 3 T compared with micro-computed tomographic measurements.

    AFFILIATION: MQIR, Department of Radiology, University of California, San Francisco, CA 94143-2520, USA. roland.krug@mrsc.ucsf.edu

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY: United States NIAMS

    GRANT: R01 AR49701

    ACRONYM: AR

    MEDLINETA: Magn Reson Imaging

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