Three-way decision based reconstruction frame for fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) has been a promising imaging tool because it allows an accurate localizaton and quantitative analysis of the fluorophore distribution in animals. It, however, is still a challenge since its reconstruction suffers from severe ill-posedness. This paper introduces a reconstruction frame based on three-way decisions (TWD) for the inverse problem of FMT. On the first stage, a reconstruction result on the whole region is obtained by a certain reconstruction algorithm. With TWD, the recovered result has been divided into three regions: fluorescent target region, boundary region, and background region. On the second stage, the boundary region and fluorescent target region have been combined into the permissible region of the target. Then a new reconstruction on the permissible region has been carried out and a new recovered result is obtained. With TWD again, the new result has been classified into three pairwise disjoint regions. And the new fluorescent target region is the final reconstructed result. Both numerical simulation experiments and a real mouse experiment are carried out to validate the feasibility and potential of the presented reconstruction frame. The results indicate that the proposed reconstuction strategy based on TWD can provide a good performance in FMT reconstruction.

[1]  Qing Li,et al.  Three-way decisions based software defect prediction , 2016, Knowl. Based Syst..

[2]  Jie Liu,et al.  Novel l 2,1-norm optimization method for fluorescence molecular tomography reconstruction. , 2016, Biomedical optics express.

[3]  Phaneendra K. Yalavarthy,et al.  Sparse Recovery Methods Hold Promise for Diffuse Optical Tomographic Image Reconstruction , 2014, IEEE Journal of Selected Topics in Quantum Electronics.

[4]  Huangjian Yi,et al.  Adaptive threshold method for recovered images of FMT. , 2018, Journal of the Optical Society of America. A, Optics, image science, and vision.

[5]  V. Ntziachristos,et al.  Multimodal Molecular Imaging of Integrin αvβ3 for In Vivo Detection of Pancreatic Cancer , 2014, The Journal of Nuclear Medicine.

[6]  Nicola Smania,et al.  Use of NeuroEyeCoach™ to Improve Eye Movement Efficacy in Patients with Homonymous Visual Field Loss , 2016, BioMed research international.

[7]  Vasilis Ntziachristos,et al.  Patch-based anisotropic diffusion scheme for fluorescence diffuse optical tomography--part 2: image reconstruction. , 2016, Physics in medicine and biology.

[8]  S. Arridge Optical tomography in medical imaging , 1999 .

[9]  Vasilis Ntziachristos,et al.  Hybrid System for Simultaneous Fluorescence and X-Ray Computed Tomography , 2010, IEEE Transactions on Medical Imaging.

[10]  Baoci Shan,et al.  A Dual Modality System for Simultaneous Fluorescence and Positron Emission Tomography Imaging of Small Animals , 2011, IEEE Transactions on Nuclear Science.

[11]  A. V. Savchenko,et al.  Fast multi-class recognition of piecewise regular objects based on sequential three-way decisions and granular computing , 2016, Knowl. Based Syst..

[12]  Xiaonan Li,et al.  Three-way decisions approach to multiple attribute group decision making with linguistic information-based decision-theoretic rough fuzzy set , 2018, Int. J. Approx. Reason..

[13]  Vasilis Ntziachristos,et al.  An Inversion Scheme for Hybrid Fluorescence Molecular Tomography Using a Fuzzy Inference System , 2016, IEEE Transactions on Medical Imaging.

[14]  Jianwen Luo,et al.  Iterative Correction Scheme Based on Discrete Cosine Transform and L1 Regularization for Fluorescence Molecular Tomography With Background Fluorescence , 2016, IEEE Transactions on Biomedical Engineering.

[15]  Simon Arridge,et al.  Patch-based anisotropic diffusion scheme for fluorescence diffuse optical tomography--part 1: technical principles. , 2016, Physics in medicine and biology.

[16]  Jianwen Luo,et al.  In vivo tomographic imaging with fluorescence and MRI using tumor-targeted dual-labeled nanoparticles , 2013, International journal of nanomedicine.

[17]  Michael S. Patterson,et al.  Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region , 2010, Biomedical optics express.

[18]  Rebecca Richards-Kortum,et al.  Optical molecular imaging agents for cancer diagnostics and therapeutics. , 2006, Nanomedicine.

[19]  Yujie Lu,et al.  Small animal fluorescence and bioluminescence tomography: a review of approaches, algorithms and technology update , 2014, Physics in medicine and biology.

[20]  Vasilis Ntziachristos,et al.  Optical and Optoacoustic Model-Based Tomography: Theory and current challenges for deep tissue imaging of optical contrast , 2015, IEEE Signal Processing Magazine.

[21]  V. Ntziachristos,et al.  FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography–X-ray computed tomography , 2012, Nature Methods.

[22]  R. Weissleder,et al.  Fluorescence molecular tomography resolves protease activity in vivo , 2002, Nature Medicine.

[23]  Yiyu Yao,et al.  The superiority of three-way decisions in probabilistic rough set models , 2011, Inf. Sci..

[24]  M. Schweiger,et al.  The finite element method for the propagation of light in scattering media: boundary and source conditions. , 1995, Medical physics.

[25]  Jianwen Luo,et al.  Fast reconstruction of fluorescence molecular tomography via a permissible region extraction strategy. , 2014, Journal of the Optical Society of America. A, Optics, image science, and vision.

[26]  Philippe Pouliot,et al.  Hybrid FMT-MRI applied to in vivo atherosclerosis imaging. , 2014, Biomedical optics express.

[27]  Mário A. T. Figueiredo,et al.  Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.