Improving mesoscopic fluorescence molecular tomography through data reduction.

Mesoscopic fluorescence molecular tomography (MFMT) is a novel imaging technique that aims at obtaining the 3-D distribution of molecular probes inside biological tissues at depths of a few millimeters. To achieve high resolution, around 100-150μm scale in turbid samples, dense spatial sampling strategies are required. However, a large number of optodes leads to sizable forward and inverse problems that can be challenging to compute efficiently. In this work, we propose a two-step data reduction strategy to accelerate the inverse problem and improve robustness. First, data selection is performed via signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) criteria. Then principal component analysis (PCA) is applied to further reduce the size of the sensitivity matrix. We perform numerical simulations and phantom experiments to validate the effectiveness of the proposed strategy. In both in silico and in vitro cases, we are able to significantly improve the quality of MFMT reconstructions while reducing the computation times by close to a factor of two.

[1]  David A Boas,et al.  Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units. , 2009, Optics express.

[2]  Xavier Intes,et al.  Hyperspectral time-resolved wide-field fluorescence molecular tomography based on structured light and single-pixel detection. , 2015, Optics letters.

[3]  Jianwen Luo,et al.  Accelerated image reconstruction in fluorescence molecular tomography using dimension reduction , 2013, Biomedical optics express.

[4]  David A Boas,et al.  Laminar optical tomography: demonstration of millimeter-scale depth-resolved imaging in turbid media. , 2004, Optics letters.

[5]  S. Arridge,et al.  Optical tomography: forward and inverse problems , 2009, 0907.2586.

[6]  Xavier Intes,et al.  High-Resolution Mesoscopic Fluorescence Molecular Tomography Based on Compressive Sensing , 2015, IEEE Transactions on Biomedical Engineering.

[7]  Alex Cable,et al.  Three-dimensional coregistered optical coherence tomography and line-scanning fluorescence laminar optical tomography. , 2009, Optics letters.

[8]  Vasilis Ntziachristos,et al.  Compression of Born ratio for fluorescence molecular tomography/x-ray computed tomography hybrid imaging: methodology and in vivo validation. , 2013, Optics letters.

[9]  Xavier Intes,et al.  The integration of 3-D cell printing and mesoscopic fluorescence molecular tomography of vascular constructs within thick hydrogel scaffolds. , 2012, Biomaterials.

[10]  Xavier Intes,et al.  Mesoscopic fluorescence molecular tomography of reporter genes in bioprinted thick tissue , 2013, Journal of biomedical optics.

[11]  Xavier Intes,et al.  Wide-field fluorescence molecular tomography with compressive sensing based preconditioning. , 2015, Biomedical optics express.

[12]  Xavier Intes,et al.  Mesoscopic Fluorescence Molecular Tomography for Evaluating Engineered Tissues , 2015, Annals of Biomedical Engineering.

[13]  Qinggong Tang,et al.  In Vivo Mesoscopic Voltage-Sensitive Dye Imaging of Brain Activation , 2015, Scientific Reports.

[14]  Ge Wang,et al.  L(p) regularization for early gate fluorescence molecular tomography. , 2014, Optics letters.

[15]  Xavier Intes,et al.  Comparison of Monte Carlo methods for fluorescence molecular tomography-computational efficiency. , 2011, Medical physics.

[16]  Vasilis Ntziachristos,et al.  Reconstruction of fluorescence distribution hidden in biological tissue using mesoscopic epifluorescence tomography. , 2011, Journal of biomedical optics.

[17]  D Boas,et al.  Transport-based image reconstruction in turbid media with small source-detector separations. , 2000, Optics letters.

[18]  Xavier Intes,et al.  Compressive hyperspectral time-resolved wide-field fluorescence lifetime imaging. , 2017, Nature photonics.

[19]  Jianwen Luo,et al.  Fast Reconstruction in Fluorescence Molecular Tomography Using Data Compression of Intra- and Inter-Projections , 2015 .

[20]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[21]  J. S. Silva,et al.  Fast volumetric registration method for tumor follow‐up in pulmonary CT exams , 2011, Journal of applied clinical medical physics.

[22]  Frédéric Lesage,et al.  Laminar optical tomography of the hemodynamic response in the lumbar spinal cord of rats. , 2010, Optics express.

[23]  Xavier Intes,et al.  Mesoscopic fluorescence tomography of a photosensitizer (HPPH) 3D biodistribution in skin cancer. , 2014, Academic radiology.