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Paul Sajda
Researcher at Columbia University
Publications - 261
Citations - 9050
Paul Sajda is an academic researcher from Columbia University. The author has contributed to research in topics: Electroencephalography & EEG-fMRI. The author has an hindex of 45, co-authored 243 publications receiving 8015 citations. Previous affiliations of Paul Sajda include United States Army Research Laboratory & Sarnoff Corporation.
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Spectrum separation resolves partial-volume effect of MRSI as demonstrated on brain tumor scans.
TL;DR: The proposed spectral analysis method can improve the effectiveness of MRSI as a diagnostic tool and is reflected in improved discrimination between high‐grade and low‐grade gliomas, which demonstrates the physiological relevance of the extracted spectra.
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Removal of BCG Artifacts Using a Non-Kirchhoffian Overcomplete Representation
TL;DR: It is shown that the overcomplete representation method for removing BCG artifacts results in better single-trial classification performance compared to the conventional approaches, indicating that the derived neural activity in this representation retains the complex information in the trial-to-trial variability.
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Prospective active marker motion correction improves statistical power in BOLD fMRI
Jordan Muraskin,Melvyn B. Ooi,Robin I. Goldman,Sascha Krueger,William J. Thomas,Paul Sajda,Truman R. Brown +6 more
TL;DR: A prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction and shows that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction.
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Multi-resolution and wavelet representations for identifying signatures of disease.
TL;DR: This paper reviews wavelets, and other related multi-resolution transforms, within the context of identifying signatures for disease, and presents several examples where these transforms are applied to biomedical signal and imaging processing.
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Mosaicking and enhancement of slit lamp biomicroscopic fundus images
TL;DR: Video image acquisition and processing algorithms allow for mosaicking and enhancement of slit lamp biomicroscopic fundus images that may confer suitability for inexpensive, real time photodocumentation of disc and macular abnormalities.