R
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.
Papers
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Journal ArticleDOI
Inferring hand movement kinematics from MEG, EEG and intracranial EEG: From brain-machine interfaces to motor rehabilitation
Karim Jerbi,Juan R. Vidal,Jérémie Mattout,Emmanuel Maby,Françoise Lecaignard,Tomás Ossandón,Carlos M. Hamamé,Sarang S. Dalal,Romain Bouet,Jean-Philippe Lachaux,Richard M. Leahy,Sylvain Baillet,Line Garnero,Claude Delpuech,Olivier F. Bertrand +14 more
TL;DR: A brief review of the recent literature on electrophysiological brain signals in BMI research discusses its importance on the future of BMI research and its implications on the development of novel motor rehabilitation strategies.
Journal ArticleDOI
Model-based normalization for iterative 3D PET image reconstruction.
Bing Bai,Quanzheng Li,C H Holdsworth,Evren Asma,Yuan-Chuan Tai,Arion F. Chatziioannou,Richard M. Leahy +6 more
TL;DR: A maximum likelihood approach to joint estimation of the count-rate independent normalization factors, which is an extension of previous factored normalization methods in which separate factors for detector sensitivity, geometric response, block effects and deadtime are included.
Journal ArticleDOI
Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography.
TL;DR: The on-the-fly approach to incorporating the forward model into the solution of the inverse problem can lead to substantial reductions in total cost when combined with a rapidly converging iterative algorithm.
Journal ArticleDOI
Individual parcellation of resting fMRI with a group functional connectivity prior.
Minqi Chong,Chitresh Bhushan,Anand A. Joshi,Soyoung Choi,Justin P. Haldar,David W. Shattuck,R.N. Spreng,Richard M. Leahy +7 more
TL;DR: A method for cortical parcellation that adapts a common functional atlas to produce individualized parcellations consistent with each subjects resting fMRI is described, enabling a more accurate estimation of individual subject functional areas and facilitating group analysis of functional connectivity, while maintaining consistency across individuals with a standardized topological atlas.
Book ChapterDOI
MEG-based imaging of focal neuronal current sources
TL;DR: A Bayesian formulation of the inverse problem in which a Gibbs prior is constructed to reflect the sparse focal nature of the current sources and its performance is compared with several weighted minimum norm methods.