Literature DB >> 21559137

Reply to "Comment on 'A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation'".

Haiou Shen1, Ge Wang.   

Abstract

We compare the accuracy of TIM-OS and MMCM in response to the recent analysis made by Fang [Biomed. Opt. Express 2, 1258 (2011)]. Our results show that the tetrahedron-based energy deposition algorithm used in TIM-OS is more accurate than the node-based energy deposition algorithm used in MMCM.

Entities:  

Keywords:  (170.3660) Light propagation in tissues

Year:  2011        PMID: 21559137      PMCID: PMC3087582          DOI: 10.1364/BOE.2.001265

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


Reply

Simulation speed

In [2], we compared the latest versions of several optical Monte Carlo (MC) simulation packages with our recently developed TIM-OS [1]. Particularly, MMCM was downloaded on September 29, 2010 from its website (http://mcx.sourceforgo.net/mmc) and compiled with the best setting in the package. As shown in Dr. Fang’s comment [5], he recently updated the MMCM package that now takes advantage of the SSE instructions and the Intel compiler, yielding a substantial performance gain. However, the latest MMCM still does not take the thread racing condition into account. As pointed out by Alerstam [4], thread racing may compromise data integrity. We also observed this problem in the MMCM results. It is underlined that TIM-OS photon-tetrahedron intersection style has a less computational complexity than the Plücker-coordinate scheme used in MMCM [2,5]. When we do photon-tetrahedron intersection tests, a photon is actually inside a tetrahedron. Such a tight restriction on the position of the photon greatly reduces the computational complexity. As a result, while the Plücker-coordinate algorithm utilizes all the equations in [3], the original TIM-OS algorithm only uses the popular ray-plane intersection equation.

Simulation accuracy

Figure 1 illustrates the problem in [5]. While the solid curve shows the true value , and are the values used in [5] to compare MMCM and TIM-OS. However, each datum he used had two parts: , where and were the values TIM-OS estimated at the positions and , respectively. Hence, actually was a linear interpolation of two TIM-OS results. It is not fair to compare a linearly interpolated TIM-OS result to a directly computed MMCM result.
Fig. 1

Illustration of the problem in Dr. Fang’s Comment.

Illustration of the problem in Dr. Fang’s Comment. To address this discrepancy for the problem shown in Fig. 1, we compared the results of MMCM and TIM-OS to the true value at an arbitrarily selected point . In this case, by the meshing requirements of the two simulators, the integral range for MMCM was from to and the range for TIM-OS was from to . We have Then, the relative errors for MMCM and TIM-OS were derived as Therefore . Figure 2 plots for .
Fig. 2

Comparison of MMCM and TIM-OS in terms of the relative error.

Comparison of MMCM and TIM-OS in terms of the relative error. Furthermore, we considered a more realistic example in which a pencil beam passed through an absorbing-only media, and the intensity of the light beam would obey Beer’s law along the light path. We got similar result: and for . We also set up a mesh to test MMCM and TIM-OS under the above condition. Our experimental results are in an excellent agreement with the analytical prediction. We prepared a package containing all the files for the reader to repeat the experiments, which can be downloaded from http://imaging.sbes.vt.edu/software/tim-os.
  5 in total

1.  Yet faster ray-triangle intersection (using SSE4).

Authors:  Jirí Havel; Adam Herout
Journal:  IEEE Trans Vis Comput Graph       Date:  2010 May-Jun       Impact factor: 4.579

2.  A tetrahedron-based inhomogeneous Monte Carlo optical simulator.

Authors:  H Shen; G Wang
Journal:  Phys Med Biol       Date:  2010-01-20       Impact factor: 3.609

3.  Comment on "A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation".

Authors:  Qianqian Fang
Journal:  Biomed Opt Express       Date:  2011-04-19       Impact factor: 3.732

4.  Next-generation acceleration and code optimization for light transport in turbid media using GPUs.

Authors:  Erik Alerstam; William Chun Yip Lo; Tianyi David Han; Jonathan Rose; Stefan Andersson-Engels; Lothar Lilge
Journal:  Biomed Opt Express       Date:  2010-08-23       Impact factor: 3.732

5.  A study on tetrahedron-based inhomogeneous Monte Carlo optical simulation.

Authors:  Haiou Shen; Ge Wang
Journal:  Biomed Opt Express       Date:  2010-12-03       Impact factor: 3.732

  5 in total
  1 in total

1.  Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography.

Authors:  Theresa H Lye; Kevin P Vincent; Andrew D McCulloch; Christine P Hendon
Journal:  Biophys J       Date:  2018-03-27       Impact factor: 4.033

  1 in total

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