Online object oriented Monte Carlo computational tool for the needs of biomedical optics

Conceptual engineering design and optimization of laser-based imaging techniques and optical diagnostic systems used in the field of biomedical optics requires a clear understanding of the light-tissue interaction and peculiarities of localization of the detected optical radiation within the medium. The description of photon migration within the turbid tissue-like media is based on the concept of radiative transfer that forms a basis of Monte Carlo (MC) modeling. An opportunity of direct simulation of influence of structural variations of biological tissues on the probing light makes MC a primary tool for biomedical optics and optical engineering. Due to the diversity of optical modalities utilizing different properties of light and mechanisms of light-tissue interactions a new MC code is typically required to be developed for the particular diagnostic application. In current paper introducing an object oriented concept of MC modeling and utilizing modern web applications we present the generalized online computational tool suitable for the major applications in biophotonics. The computation is supported by NVIDEA CUDA Graphics Processing Unit providing acceleration of modeling up to 340 times.

[1]  C. Tropea,et al.  Light Scattering from Small Particles , 2003 .

[2]  Alexander V. Priezzhev,et al.  Effect of photons of different scattering orders on the formation of a signal in optical low-coherence tomography of highly scattering media , 2006 .

[3]  D. Boas,et al.  Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. , 2002, Optics express.

[4]  Igor Meglinski,et al.  Coherent multiple scattering effects and Monte Carlo method , 2004 .

[5]  V. L. Kuz’min,et al.  Anomalous polarization effects during light scattering in random media , 2010 .

[6]  D. Y. Churmakov,et al.  Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation , 2003 .

[7]  L Wang,et al.  MCML--Monte Carlo modeling of light transport in multi-layered tissues. , 1995, Computer methods and programs in biomedicine.

[8]  Risto Myllylä,et al.  Simulation of polarization-sensitive optical coherence tomography images by a Monte Carlo method. , 2008, Optics letters.

[9]  Edouard Berrocal,et al.  Laser light scattering in turbid media Part I: Experimental and simulated results for the spatial intensity distribution. , 2007, Optics express.

[10]  Andrew W. Troelsen Developer's Workshop To COM And ATL 3.0 , 2000 .

[11]  I. V. Meglinsky,et al.  Modelling the sampling volume for skin blood oxygenation measurements , 2006, Medical and Biological Engineering and Computing.

[12]  Ge Wang,et al.  A study on tetrahedron-based inhomogeneous Monte Carlo optical simulation , 2010, Biomedical optics express.

[13]  Risto Myllylä,et al.  Simulation of optical coherence tomography images by Monte Carlo modeling based on polarization vector approach. , 2010, Optics express.

[14]  Igor Meglinski,et al.  Helicity flip of the backscattered circular polarized light , 2010, BiOS.

[15]  I. Meglinski,et al.  The concept of a unified modeling of optical radiation propagation in complex turbid media , 2008, International Conference on Advanced Optical Materials and Devices.

[16]  Igor Meglinski,et al.  Monte Carlo simulation of coherent effects in multiple scattering , 2005, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  Jessica Ramella-Roman,et al.  Three Monte Carlo programs of polarized light transport into scattering media: part I. , 2005, Optics express.

[18]  Nishith Pathak Pro WCF 4: Practical Microsoft SOA Implementation , 2011 .

[19]  Matthew MacDonald Pro WPF in C# 2010: Windows Presentation Foundation in .NET 4 , 2009 .

[20]  Jie Cheng,et al.  Programming Massively Parallel Processors. A Hands-on Approach , 2010, Scalable Comput. Pract. Exp..

[21]  I. V. Meglinski,et al.  Stochastic modeling of coherent phenomena in strongly inhomogeneous media , 2005 .

[22]  I. V. Meglinski,et al.  Image transfer through the complex scattering turbid media , 2006, Saratov Fall Meeting.

[23]  S. Prahl The Adding-Doubling Method , 1995 .

[24]  I. Meglinski,et al.  Amending of fluorescence sensor signal localization in human skin by matching of the refractive index. , 2004, Journal of biomedical optics.

[25]  Lev S. Dolin,et al.  Development of the radiative transfer theory as applied to instrumental imaging in turbid media , 2009 .

[26]  I. V. Meglinskii LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Monte Carlo simulation of reflection spectra of random multilayer media strongly scattering and absorbing light , 2001 .

[27]  Stephen R. Schach,et al.  Object-oriented and classical software engineering , 1995 .

[28]  R. Giovanelli Reflection by Semi-infinite Diffusers , 1955 .

[29]  V. L. Kuzmin,et al.  Coherent effects of multiple scattering for scalar and electromagnetic fields: Monte–Carlo simulation and Milne-like solutions , 2007 .

[30]  Costas Balas,et al.  Review of biomedical optical imaging—a powerful, non-invasive, non-ionizing technology for improving in vivo diagnosis , 2009 .

[31]  Qianqian Fang,et al.  Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates , 2010, Biomedical optics express.

[32]  Jie Cheng,et al.  CUDA by Example: An Introduction to General-Purpose GPU Programming , 2010, Scalable Comput. Pract. Exp..

[33]  S. J. Matcher,et al.  Computer simulation of the skin reflectance spectra , 2003, Comput. Methods Programs Biomed..

[34]  Leon Shklar,et al.  Web Application Architecture: Principles, Protocols and Practices , 2003 .

[35]  Laurence Moroney Microsoft Silverlight 4 Step by Step , 2010 .