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James M. Masciotti

Researcher at Columbia University

Publications -  28
Citations -  373

James M. Masciotti is an academic researcher from Columbia University. The author has contributed to research in topics: Optical tomography & Digital signal processor. The author has an hindex of 9, co-authored 26 publications receiving 349 citations.

Papers
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Journal ArticleDOI

Digital Lock-In Detection for Discriminating Multiple Modulation Frequencies With High Accuracy and Computational Efficiency

TL;DR: A novel digital lock-in detection technique for simultaneously measuring the amplitude and phase of multiple amplitude-modulated signals and can be performed as a simple matrix multiplication, which considerably reduces the computation time.
Patent

Systems and methods for digital detection of a tomographic signal

TL;DR: In this paper, an amplitude-modulated analog signal containing tomographic information, the analog signal having a modulation frequency, f λi, is converted into a digital signal at a sampling frequency f s, to produce a number of samples, K. The signal amplitude is computed based on the filtered in-phase signal component and the filtered quadrature signal component, the signal amplitude being representative of the tomography information.
Journal ArticleDOI

Digital-signal-processor-based dynamic imaging system for optical tomography.

TL;DR: First experiments on tissue phantoms show that dynamic behavior is accurately captured and spatial location can be correctly tracked using this dynamic optical tomography system.
Journal ArticleDOI

The absence of the calcium-buffering protein calbindin is associated with faster age-related decline in hippocampal metabolism.

TL;DR: The results suggest that the decrease in CB that occurs during normal aging is involved in age‐related hippocampal metabolic decline, and the value of using multiple MRI techniques in transgenic mice to investigate mechanisms involved in the functional and structural changes that occur during aging is illustrated.
Patent

Digital signal processor-based detection system, method, and apparatus for optical tomography

TL;DR: In this paper, a unique manipulation of an ordinary averaging filter optimized for sources discrimination and the consequent sampling constraints is presented as a novel filtering scheme for the lock-in detection.