A 3D Location Method of Bioluminescence Light Source Based on Multi-view Projection Surface Reconstruction
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摘要: 在自发荧光断层成像(Bioluminescent tomography imaging,BLT)中,双模态融合(光学模态与结构模态)可充分利用结构模态提供的高精度3D几何结构,重建三维表面荧光光通量分布,进而实现小动物内部荧光光源定位.然而,与纯光学模态相比,双模态融合存在采集系统复杂、成本高、数据处理繁琐及存在电离辐射(如CT)等问题.因此,研究基于纯光学3D几何结构的自发荧光光源定位方法对BLT具有重要意义. 本文在搭建纯光学自发荧光断层系统(All-optical bioluminescence tomography system,AOBTS)的基础上,提出一种基于多角度光学投影表面重建的三维自发荧光光源定位方法. 本方法由基于多角度光学投影的3D表面重建、多角度荧光无缝融合、荧光光通量的量化校正以及自发荧光内部光源重建4部分组成. 通过真实小鼠内部植入荧光光源实验表明,与传统纯光学方法相比,本文提出方法不仅改进了3D表面重建方法,而且增加了多角度荧光无缝融合,可实现真实小鼠的三维自发荧光光源定位,初步实验证明具有小动物预临床实验潜力.Abstract: In bioluminescent tomography imaging (BLT), dual-modality fusion (optical modality and structural modality) can make full use of high accuracy 3D geometrical structures provided by structural modality reconstruct 3D surface light flux distribution and bioluminescence inner light source reconstruction. However, compared with the all-optical modality, dual-modality fusion has the problems of complicated fusion system, high cost compared with all-optical system, multifarious and exhaustive date processing, and ionizing radiation (for example, CT). Therefore, the 3D location method of bioluminescence light source based on pure optical 3D geometrical structures has significance for BLT. In this paper, we present a 3D location method of bioluminescence light source based on multi-view projection surface reconstruction, and an all-optical bioluminescence tomography system (AOBTS) is developed for this method. The method consists of 3D surface reconstruction based on multi-view optical projection, multi-view luminescent seamless integration, calibration and quantification of the surface light flux and internal bioluminescence reconstruction. An in-vivo BALB/C mouse with an implanted luminescent light source are used to evaluate the performance of the new method. Compared with the conventional optical methods, the new method improves not only the 3D surface reconstruction method but also the multi-view luminescent seamless integration. It has realized 3D real mouse bioluminescence light source localization, and the preliminary test proves its potential application in clinical trial.
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[1] Ntziachristos V, Ripoll J, Wang L V, Weissleder R. Looking and listening to light: the evolution of whole-body photonic imaging. Nature Biotechnology, 2005, 23(3): 313-320 [2] [2] Gross S, Gammon S T, Moss B L, Rauch D, Harding J, Heinecke J W, Ratner L, Piwnica-Worms D. Bioluminescence imaging of myeloperoxidase activity in vivo. Nature Medicine, 2009, 15(4): 455-461 [3] [3] Naumann E A, Kampff A R, Prober D A, Schier A F, Engert F. Monitoring neural activity with bioluminescence during natural behavior. Nature Neuroscience, 2010, 13(4): 513-520 [4] [4] Zhang C, Yan Z, Arango M E, Painter C L, Anderes K. Advancing bioluminescence imaging technology for the evaluation of anticancer agents in the MDA-MB-435-HAL-Luc mammary fat pad and subrenal capsule tumor models. Clinical Cancer Research, 2009, 15(1): 238-246 [5] Li Hui, Dai Ru-Wei. Development of in vivo optieal imaging. Acta Automatica Sinica, 2008, 34(12): 1449-1457(李慧, 戴汝为. 在体生物光学成像技术的研究进展. 自动化学报, 2008, 34(12): 1449-1457) [6] [6] Ma X B, Deng K X, Xue Z W, Liu X Y, Zhu S P, Qin C H, Yang X, Tian J. Novel registration for microcomputed tomography and bioluminescence imaging based on iterated optimal projection. Journal of Biomedical Optics, 2013, 18(2): 26013-26013 [7] [7] Lu Y J, Machado H B, Bao Q N, Stout D, Herschman H, Chatziioannou A F. In vivo mouse bioluminescence tomography with radionuclide-based imaging validation. Molecular Imaging and Biology, 2011, 13(1): 53-58 [8] [8] Wang G, Li Y, Jiang M. Uniqueness theorems in bioluminescence tomography. Medical Physics, 2004, 31(8): 2289-2299 [9] [9] Wang G, Cong W X, Durairaj K, Qian X, Shen H O, Sinn P, Hoffman E, Mclennan G, Henry M. In vivo mouse studies with bioluminescence tomography. Optics Express, 2006, 14(17): 7801-7809 [10] Lasser T, Soubret A, Ripoll J, Ntziachristos V. Surface reconstruction for free-space 360o fluorescence molecular tomography and the effects of animal motion. IEEE Transactions on Medical Imaging, 2008, 27(2): 188-194 [11] Ripoll J, Schulz R B, Ntziachristos V. Free-space propagation of diffuse light: theory and experiments. Physical Review Letters, 2003, 91(10): 103901 [12] Han D, Tian J, Zhu S P, Feng J C, Qin C H, Zhang B, Yang X. A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization. Optics Express, 2010, 18(8): 8630-8646 [13] Wu P, Liu K, Zhang Q, Xue Z W, Li Y B, Ning N N, Yang X, Li X D, Tian J. Detection of mouse liver cancer via a parallel iterative shrinkage method in hybrid optical/microcomputed tomography imaging. Journal of Biomedical Optics, 2012, 17(12): 126012-126012 [14] Guo W, Jia K, Tian J, Han D, Liu X Y, Wu P, Feng J C, Yang X. An efficent reconstruction method for bioluminescence tomography based on two-step iterative shrinkage approach. In: Proceedings of Medical Imaging 2012: Physics of Medical Imaging. California, USA: SPIE, 2012. 83133Y [15] Alexandrakis G, Rannou F R, Chatziioannou A F. Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study. Physics in Medicine and Biology, 2005, 50(17): 4225-4241 [16] Wu P, Hu Y,Wang K, Tian J. Bioluminescence tomography by an iterative reweighted L2 norm optimization. IEEE Trasactions on Biomedical Engineering. NewYork, USA: 2014, 61(1): 189-196 [17] Weissleder R, Pittet M J. Imaging in the era of molecular oncology. Nature, 2008, 452(7187): 580-589 [18] Shi B, Zhang B, Liu F, Luo J W, Bai J W. 360o Fourier transform profilometry in surface reconstruction for fluorescence molecular tomography. IEEE Journal of Biomedical and Health Informatics, 2011, 17(3): 681-689 [19] Chen X L, Zhao H, Qu X C, Chen D F, Wang X R, Liang J M. All-optical quantitative framework for bioluminescence tomography with non-contact measurement. International Journal of Automation and Computing, 2012, 9(1): 72-80 [20] Cong W X, Wang G, Kumar D, Liu Y, Jiang M, Wang L V, Hoffman E A, McLennan G, McCray P B, Zabner J, Cong A. Practical reconstruction method for bioluminescence tomography. Optics Express, 2005, 13(18): 6756-6771 [21] Kutulakos K N, Seitz S M. A theory of shape by space carving. International Journal of Computer Vision, 2000, 38(3): 199-218 [22] Niem W, Wingbermuhle J. Automatic reconstruction of 3D objects using a mobile monoscopic camera. In: Proceedings of the 1997 Proceedings, International Conference on Recent Advances in 3-D Digital Imaging and Modeling. Ottawa, Ont: IEEE, 1997. 173-180 [23] Potmesil M. Generating octree models of 3D objects from their silhouettes in a sequence of images. Computer Vision, Graphics, and Image Processing, 1987, 40(1): 1-29 [24] Liang C, Wong K Y K. Exact visual hull from marching cubes. In: Proceedings of the 3rd International Conference on Computer Vision Theory and Applications. Funchal, PORTUGAL: VISAPP, 2008. (2): 597-604 [25] Schweiger M, Arridge S, Hiraoka M, Delpy D. The finite element method for the propagation of light in scattering media: boundary and source conditions. Medical Physics, 1995, 22(11): 1779-1792 [26] Seitz S M, Curless B, Diebel J, Scharstein D, Szeliski R. A comparison and evaluation of multi-view stereo reconstruction algorithms. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2006. 519-528 [27] Bernardini F, Martin I M, Rushmeier H. High-quality texture reconstruction from multiple scans. IEEE Transactions on Visualization and Computer Graphics, 2001, 7(4): 318-332 [28] Rocchini C, Cignoni P, Montani C, Scopigno R. Acquiring, stitching and blending diffuse appearance attributes on 3D models. The Visual Computer, 2002, 18(3): 186-204 [29] Goldlcke B, Cremers D. A Superresolution Framework for High-Accuracy Multiview Reconstruction. Pattern Recognition: Springer, 2009. 342-351 [30] Baumberg A. Blengding images for texturing 3D models. In: Proceedings of the British Machine Conference. Cardiff, UK: BMVA Press, 2002. 1-38 [31] Chen X L, Gao X B, Qu X C, Chen D F, Ma X P, Liang J M, Tian J. Generalized free-space diffuse photon transport model based on the influence analysis of a camera lens diaphragm. Applied Optics, 2010, 49(29): 5654-5664 [32] Zhu Shou-Ping. Research on Micro-Computed Tomography and its Multimodality Integration with Bioluminescence Tomography [Ph.D. dissertation], Graduate School of Chinese Academy of Sciences, China, 2010 (朱守平. 微型计算机断层成像及其与自发荧光断层成像多模态融合的研究 [博士学位论文], 中国科学院研究生院, 中国, 2010) [33] Liu J T, Wang Y B, Qu X C, Li X S, Ma X S, Han R Q, Hu Z H, Chen X L, Sun D D, Zhang R Q, Chen D F, Chen D, Chen X Y, Liang J M, Cao F, Tian J. In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models. Optics Express, 2010, 18(12): 13102-13113 [34] Arridge S R. Optical tomography in medical imaging. Inverse Problems, 1999, 15(2): R41, DOI: 10.1088/0266-5611/ 15/2/022
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