Imaging Components, Systems, and Processing

Fluorescence molecular tomographic image reconstruction based on reduced measurement data

[+] Author Affiliations
Wei Zou, Jiajun Wang

Soochow University, School of Electronic and Information Engineering, Shizi Street, Suzhou 215006, China

Hong Kong Polytechnic University, Department of Electronic and Information Engineering, Hong Kong, China

The University of Sydney, School of Information Technologies, Sydney 2006, Australia

David Dagan Feng

Hong Kong Polytechnic University, Department of Electronic and Information Engineering, Hong Kong, China

The University of Sydney, School of Information Technologies, Sydney 2006, Australia

Shanghai Jiao Tong University, Med-X Research Institute, Shanghai 200030, China

Erxi Fang

Soochow University, School of Electronic and Information Engineering, Shizi Street, Suzhou 215006, China

Opt. Eng. 54(7), 073114 (Jul 27, 2015). doi:10.1117/1.OE.54.7.073114
History: Received December 31, 2014; Accepted July 2, 2015
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Abstract.  The analysis of fluorescence molecular tomography is important for medical diagnosis and treatment. Although the quality of reconstructed results can be improved with the increasing number of measurement data, the scale of the matrices involved in the reconstruction of fluorescence molecular tomography will also become larger, which may slow down the reconstruction process. A new method is proposed where measurement data are reduced according to the rows of the Jacobian matrix and the projection residual error. To further accelerate the reconstruction process, the global inverse problem is solved with level-by-level Schur complement decomposition. Simulation results demonstrate that the speed of the reconstruction process can be improved with the proposed algorithm.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Wei Zou ; Jiajun Wang ; David Dagan Feng and Erxi Fang
"Fluorescence molecular tomographic image reconstruction based on reduced measurement data", Opt. Eng. 54(7), 073114 (Jul 27, 2015). ; http://dx.doi.org/10.1117/1.OE.54.7.073114


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