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Overview

Lab Members

Britton Chance / John Schotland / Warren Warren / Xavier Intes / Gunay Yurtsever / David Busch / Vadun Narjek / George Panasyuk

About the Core

Our objective is to develop innovative optical imaging technologies, optimal strategies for integrated optical and MRI methods, and theoretical algorithms required for high-resolution optical image reconstruction. Working closely with collaborators, the technologies we are working to develop will be used to diagnose cancer and gain detailed understanding of cancer metabolism, brain and muscle function under different pathophysiological conditions.

Active Research

Optical Functional Imaging

Our efforts deal with the development of multi-source, multi-detector, multi-wave length optical imaging systems for NIR spectroscopy and imaging. Specifically, we are investigating in-magnet coupling for co-registering optical imaging data with MRI, provided through the use of (i) a multi-source detector fiber coupled system and (ii) a novel remote sensing system which employs flying spot technology. Performing experiments on model systems as well as on human brain, breast and muscle tissue in vivo can show the efficacy of this instrumentation in obtaining high-resolution images.

Two-photon Metabolic Imaging

The primary objective of this project is to develop two-photon absorption/fluorescence laser scanning for deep tissue imaging. By employing shaped pulses for two-photon fluorescence imaging and two-photon absorption in various near-infrared water windows, methods for imaging deep tissue of functional brain and other tumor imaging with microscopic resolution are being investigated. These methodologies can be validated by performing experiments on ex vivo tissue and on animal models.

Image Reconstruction in Diffusion Tomography

The goal of the proposed research is to develop substantially improved image reconstruction algorithms for optical tomography. Specifically, computationally efficient reconstruction algorithms for high-resolution three-dimensional imaging are being investigated. To achieve this goal, we plan to take advantage of recent advances in both analytic and numerical approaches to the inverse scattering problem for diffuse light. In particular, we aim to 1) investigate image reconstruction algorithms which derive from analytic solutions to the linear inverse problem, 2) investigate image reconstruction algorithms which derive from analytic solutions to the nonlinear inverse problem, and 3) optimize the above reconstruction algorithms in the planar geometry.