Fast image reconstruction in fluoresence optical tomography using data compression

Abstract

We present a method for fast reconstruction in flourescence optical tomography with very large data sets. In recent reports, CCD cameras at multiple positions have been used to collect optical measurements, producing more than ${10}^7$ data samples. This makes storage of the full system Jacobian infeasible, and so data are usually subsampled. The method reported here allows use of the full data set, via image compression methods, and explicit construction of the (small) Jacobian, meaning optimal inversion methods can be applied, and thus leading to very fast reconstruction.

© 2010 Optical Society of America

Multiple-view fluorescence optical tomography reconstruction using compression of experimental data

Nicolas Ducros, Andrea Bassi, Gianluca Valentini, Martin Schweiger, Simon Arridge, and Cosimo D’Andrea
Opt. Lett. 36(8) 1377-1379 (2011)

Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction

Xu Cao, Xin Wang, Bin Zhang, Fei Liu, Jianwen Luo, and Jing Bai
Biomed. Opt. Express 4(1) 1-14 (2013)

A matrix-free algorithm for multiple wavelength fluorescence tomography

Athanasios D Zacharopoulos, Pontus Svenmarker, Johan Axelsson, Martin Schweiger, Simon R Arridge, and Stefan Andersson-Engels
Opt. Express 17(5) 3025-3035 (2009)

A wavelet-based single-view reconstruction approach for cone beam x-ray luminescence tomography imaging

Xin Liu, Hongkai Wang, Mantao Xu, Shengdong Nie, and Hongbing Lu
Biomed. Opt. Express 5(11) 3848-3858 (2014)

Spatial-frequency-compression scheme for diffuse optical tomography with dense sampling dataset

Xiaoqing Zhou, Ying Fan, Qiang Hou, Huijuan Zhao, and Feng Gao
Appl. Opt. 52(9) 1779-1792 (2013)