Paper
26 October 2004 Cortical constraint method for diffuse optical brain imaging
Author Affiliations +
Abstract
We develop a parametric, shape-based image reconstruction algorithm for the joint reconstruction of the optical absorption and diffusion coefficients in the brain using diffuse optical tomographic data. Specifically, we study the recovery of the geometry of an unknown number of 2D closed contours located on a 2D manifold (the cortex) in 3-space. We describe an approach for a brain model in which we assume the existence of a one-to-one map from the surface of the cortex to a subset of the plane. We use a new, parametric level set approach to map shapes on the plane to structures on the cortex. Our optimization-based reconstruction algorithm evolves shapes on the plane while finding absorption and reduced scattering values inside each shape. Preliminary numerical simulation results show the promise of our approach.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Misha Kilmer, Eric Miller, Marco Enriquez, and David Boas "Cortical constraint method for diffuse optical brain imaging", Proc. SPIE 5559, Advanced Signal Processing Algorithms, Architectures, and Implementations XIV, (26 October 2004); https://doi.org/10.1117/12.559745
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Absorption

Diffusion

Brain

3D image reconstruction

3D modeling

Scattering

Reconstruction algorithms

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