Improving diffuse optical tomography with structural a priori from fluorescence diffuse optical tomography

We obtain absorption and scattering reconstructed images by incorporating a priori information of target location obtained from fluorescence diffuse optical tomography (FDOT) into the diffuse optical tomography (DOT). The main disadvantage of DOT lies in the low spatial resolution resulting from highly scattering nature of tissue in the near-infrared (NIR), but one can use it to monitor hemoglobin concentration and oxygen saturation simultaneously, as well as several other cheomphores such as water, lipids, and cytochrome-c-oxidase. Up to date, extensive effort has been made to integrate DOT with other imaging modalities such as MRI, CT, to obtain accurate optical property maps of the tissue. However, the experimental apparatus is intricate. In this study, DOT image reconstruction algorithm that incorporates a prior structural information provided by FDOT is investigated in an attempt to optimize recovery of a simulated optical property distribution. By use of a specifically designed multi-channel time-correlated single photon counting system, the proposed scheme in a transmission mode is experimentally validated to achieve simultaneous reconstruction of the fluorescent yield, lifetime, absorption and scattering coefficient. The experimental results demonstrate that the quantitative recovery of the tumor optical properties has doubled and the spatial resolution improves as well by applying the new improved method.

[1]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Feng Gao,et al.  Time-resolved diffuse optical tomography and its application to in vitro and in vivo imaging. , 2007, Journal of biomedical optics.

[3]  Feng Gao,et al.  A self-normalized, full time-resolved method for fluorescence diffuse optical tomography. , 2008, Optics express.

[4]  Hamid Dehghani,et al.  A microcomputed tomography guided fluorescence tomography system for small animal molecular imaging. , 2009, The Review of scientific instruments.

[5]  Tianzi Jiang,et al.  Improving image quality of diffuse optical tomography with a projection-error-based adaptive regularization method. , 2008, Optics express.

[6]  Feng Gao,et al.  Simultaneous fluorescence yield and lifetime tomography from time-resolved transmittances of small-animal-sized phantom. , 2010, Applied optics.

[7]  Michael Unser,et al.  Sparsity-Driven Reconstruction for FDOT With Anatomical Priors , 2011, IEEE Transactions on Medical Imaging.

[8]  Yuting Lin,et al.  Quantitative fluorescence tomography using a combined tri-modality FT/DOT/XCT system , 2010, Optics express.

[9]  Alessandro Torricelli,et al.  Time-resolved scanning system for double reflectance and transmittance fluorescence imaging of diffusive media. , 2008, The Review of scientific instruments.

[10]  S. Achilefu,et al.  In vivo fluorescence lifetime tomography. , 2009, Journal of biomedical optics.

[11]  Hanli Liu,et al.  Development of a compensation algorithm for accurate depth localization in diffuse optical tomography. , 2010, Optics letters.

[12]  Xin Liu,et al.  Unmixing Dynamic Fluorescence Diffuse Optical Tomography Images With Independent Component Analysis , 2011, IEEE Transactions on Medical Imaging.

[13]  B. Pogue,et al.  Near-infrared (NIR) tomography breast image reconstruction with a priori structural information from MRI: algorithm development for reconstructing heterogeneities , 2003 .

[14]  K Rajan,et al.  Accelerated gradient based diffuse optical tomographic image reconstruction. , 2011, Medical physics.