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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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Journal ArticleDOI

Effective connectivity differs between focal cortical dysplasia types I and II.

TL;DR: In this article, the amplitude and latency of CCEP responses following ictal-onset single-pulse electrical stimulation (iSPES) were analyzed in 25 FCD patients with drug-resistant focal epilepsy who underwent intracranial evaluation with stereo-electroencephalography (SEEG).
Proceedings ArticleDOI

Viability of sharing MEG data using minimum-norm imaging

TL;DR: This work uses data from left median nerve stimulation experiments on four subjects at each of three sites on two runs occurring on consecutive days for each site to analyze whether pooling MEG data across sites is more variable than aggregating MEGData across runs when estimating significant cortical activity.
Journal ArticleDOI

Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity

TL;DR: In this article , the authors present a complete pipeline, integrated into the Brainstorm software, that allows users to automatically generate an individual and accurate head model based on the subject's MRI and calculate the electromagnetic forward solution using the finite element method (FEM).
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Realistic head modeling of electromagnetic brain activity: An integrated Brainstorm pipeline from MRI data to the FEM solution

TL;DR: A complete pipeline is presented that allows users to generate an individual and accurate head model from the MRI and then calculate the electromagnetic forward solution using the finite element method (FEM).
Proceedings ArticleDOI

Matched subspace detection for dynamic PET: an ROC phantom study for MAP reconstruction

TL;DR: A modified matched subspace detection algorithm to assist in the detection of small tumors in dynamic PET images using the time activity curves (TACs) that characterize the uptake of PET tracers.