Nth-order linear algorithm for diffuse correlation tomography
نویسندگان
چکیده
منابع مشابه
A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues.
Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in h...
متن کاملExtraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation.
Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αDB ) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction o...
متن کاملA computational algorithm for special nth-order pentadiagonal Toeplitz determinants
In this short note, we present a fast and reliable algorithm for evaluating special nth-order pentadiagonal Toeplitz determinants in linear time. The algorithm is suited for implementation using Computer Algebra Systems (CAS) such as MACSYMA and MAPLE. Two illustrative examples are given. 2007 Elsevier Inc. All rights reserved.
متن کاملVerified integration of linear nth order ODEs using large steps
The solution y(x) of an IVP for a linear ODE with analytic coefficient functions is represented as a power series. A high–order Taylor polynomial is used for an approximate numerical solution. The Taylor remainder series is rigorously estimated by some geometric series. The method has been implemented and tested on a computer. Guaranteed enclosures are achieved by taking into account all roundo...
متن کاملAn Efficient Method for Model Reduction in Diffuse Optical Tomography
We present an efficient method for the reduction of model equations in the linearized diffuse optical tomography (DOT) problem. We first implement the maximum a posteriori (MAP) estimator and Tikhonov regularization, which are based on applying preconditioners to linear perturbation equations. For model reduction, the precondition is split into two parts: the principal components are consid...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biomedical Optics Express
سال: 2018
ISSN: 2156-7085,2156-7085
DOI: 10.1364/boe.9.002365