Ghosh, Pratik and Laidlaw, David H. and Fleischer, Kurt W. and Barr, Alan H. and Jacobs, Russell E. (1995) Pure phase-encoded MRI and classification of solids. IEEE Transactions on Medical Imaging, 14 (3). pp. 616-620. ISSN 0278-0062. http://resolver.caltech.edu/CaltechAUTHORS:GHOieeetmi95
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Here, the authors combine a pure phase-encoded magnetic resonance imaging (MRI) method with a new tissue-classification technique to make geometric models of a human tooth. They demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer. In solid-state imaging, confounding line-broadening effects are typically eliminated using coherent averaging methods. Instead, the authors circumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice of the phase-encode time in the MRI protocol, the authors differentiate enamel and dentine sufficiently to successfully apply a new classification algorithm. This tissue-classification algorithm identifies the distribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, the authors treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than one material. They use the distribution of MR image intensities within each voxel-sized volume to estimate the relative proportion of each material using a probabilistic approach. This combined approach, involving MRI and data classification, is directly applicable to bone imaging and hard-tissue contrast-based modeling of biological solids.
|Additional Information:||© Copyright 1995 IEEE. Reprinted with permission. Manuscript received October 7, 1994; revised May 8, 1995. This work was supported by grants from the NSF (ASC-89-20219), as part of the NSF/ARPA STC for Computer Graphics and Scientific Visualization, by the DOE (DE-FG03-92ER25134). as part of the Center for Research in Computational Biology, by the National Institute on Drug Abuse and the National Institute of Mental Health, as part of the Human Brain Project, and by the Beckman Institute at the California Institute of Technology. This work was also supported by Apple, DEC, Hewlett Packard, and IBM. The Editor responsible for coordinating the review of this paper and recommending its publication was M.W. Vannier. The authors would like to thank J. Allman, Division of Biology, for providing the teeth and helpful discussions, as well as P.T. Narasimhan, Biological Imaging Center, Division of Biology, for providing stimulating discussions. They would also like to thank S. Gravina, Bruker Instruments (MA), for providing technical assistance, and D. De Sha, Biological Imaging Center, for graciously assisting with editing the manuscript.|
|Subject Keywords:||biomedical NMR; bone; image classification; medical image processing|
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|Deposited On:||12 Mar 2008|
|Last Modified:||30 Dec 2015 23:35|
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