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Richard M. Leahy

Researcher at University of Southern California

Publications -  419
Citations -  27317

Richard M. Leahy is an academic researcher from University of Southern California. The author has contributed to research in topics: Iterative reconstruction & Imaging phantom. The author has an hindex of 70, co-authored 406 publications receiving 24876 citations. Previous affiliations of Richard M. Leahy include Los Alamos National Laboratory & Johns Hopkins University School of Medicine.

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Digimouse: a 3D whole body mouse atlas from CT and cryosection data

TL;DR: A three-dimensional (3D) whole body mouse atlas is constructed from coregistered x-ray CT and cryosection data of a normal nude male mouse and simulations of 3D bioluminescence and PET image reconstruction are included.
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Iterative reconstruction techniques in emission computed tomography.

TL;DR: A review of recent progress in developing statistically based iterative techniques for emission computed tomography describes the different formulations of the emission image reconstruction problem and their properties and describes the numerical algorithms used for optimizing these functions.
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Resolution and noise properties of MAP reconstruction for fully 3-D PET

TL;DR: The authors show that the approximations provide reasonably accurate estimates of contrast recovery and covariance of MAP reconstruction for priors with quadratic energy functions, and describe how these analytical results can be used to achieve near-uniform contrast recovery throughout the reconstructed volume.
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Recursive MUSIC: A framework for EEG and MEG source localization

TL;DR: R-MUSIC can easily extract multiple asynchronous dipolar sources that are difficult to find using the original MUSIC scan and is applied to the more general IT model and shows results for combinations of fixed, rotating, and synchronous dipoles.
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Source localization using recursively applied and projected (RAP) MUSIC

TL;DR: A new method for source localization is described that is based on a modification of the well-known MUSIC algorithm, and a general form of the RAP-MUSIC algorithm is described for the case of diversely polarized sources.