Paper
29 February 2012 A CT-analogous method for high-resolution fluorescence molecular tomography
Author Affiliations +
Proceedings Volume 8216, Multimodal Biomedical Imaging VII; 82160W (2012) https://doi.org/10.1117/12.905625
Event: SPIE BiOS, 2012, San Francisco, California, United States
Abstract
In vivo biomedical imaging using near-infrared light must overcome the effects of highly light scattering, which limit the spatial resolution and affect image quality. The high-resolution, sensitive and quantitative fluorescence imaging tool is an urgent need for the applications in small-animal imaging and clinical cancer research. A CT-analogous method for fluorescence molecular tomography (FMT) on small-animal-sized models is presented to improve the spatial resolution of FMT to a limit of several millimeters, depending on the size of the tissue region to be imaged. The method combines FMT physics with the filtered back-projection scheme for image reconstruction of the fan-beam computed tomography, based on the early-photon detection of time-resolved optical signals, and is suitable for two-dimensional (2D) imaging of small size biological models. By use of a normalized Born formulation for the inversion, the algorithm is validated using full time-resolved simulated data for 2D phantom that are generated from a hybrid finite-element and finite-time-difference photon diffusion modeling, and its superiority in the improvement of the spatial resolution is demonstrated by imaging different target-to-background contrast ratios.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiao Li, Feng Gao, Qingzhen Zhu, Fenghui Li, Xin Wang, Limin Zhang, and Huijuan Zhao "A CT-analogous method for high-resolution fluorescence molecular tomography", Proc. SPIE 8216, Multimodal Biomedical Imaging VII, 82160W (29 February 2012); https://doi.org/10.1117/12.905625
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KEYWORDS
Luminescence

Sensors

Atrial fibrillation

Spatial resolution

Data modeling

Reconstruction algorithms

Tomography

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