1 / 16

Mont-Carlo simulation of OCT structural images of subcutaneous blood vessels

This study presents a method to simulate optical coherence tomography (OCT) structural images of subcutaneous blood vessels using the Monte Carlo method. The effectiveness of the simulation technique is validated by comparing the simulated and experimentally acquired A-scans. The simulation is based on voxel representation of the biological object and takes into account the optical properties of the different layers. The simulated images show good correlation with experimental data. This technique allows for high precision simulation of OCT for biological objects.

jroque
Download Presentation

Mont-Carlo simulation of OCT structural images of subcutaneous blood vessels

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Mont-Carlo simulation of OCT structural images of subcutaneous blood vessels PetrovD.A., Potlov A.Yu., Proskurin S.G. Biomedical engineering, TSTU, Russia http://bmt.tstu.ru/ http://spros.tamb.ru/ spros@tamb.ru Saratov Fall Meeting 2016

  2. Abstract • A method of optical coherence tomography (OCT) structural images simulation using the Monte Carlo method with the help of multithreaded computation is described. Simulated structural images of subcutaneous blood vessel are presented. • Biological object inner structure simulated with set of cubic volumetric shapes based on the experimental results. B-scans of the inner structure are demonstrated instead of analytical representation of the boundary geometry. Effectiveness of the described simulation technique is checked by the comparison of the simulated and experimentally acquired A-scans. • For this purpose, the biological object is considered as a set of 3D elements that allow simulation of media, structure of which cannot be described analytically. Each element is characterized by its refractive index and anisotropy, scattering and absorption coefficients. • The probability of reflection on the interface of elements with different refractive indices is determined using Fresnel equations. The photon mean free path is calculated using total attenuation coefficient. The possibility of simulation and visualization of biological objects with high scattering, such as blood vessels and blood flow was demonstrated.

  3. Voxel representation Biological object inner structure simulation based on voxels and analytical expressions

  4. Object structure simulation Biological object inner structure simulation based on the experimental B-scan

  5. Simulation algorithm

  6. Photon packet launching Photon packet start position: where - beam waist, - azimuthal angle - current A-scan index - uniformly distributed random number between 0 and 1 Photon packet initial position: where - focal distance

  7. Photon packet launching And energy absorption Step size of photon packet : where - scattering coefficient Photon packet energy absorption calculated using Beer-Lambert law: - statistical weight of photon packet where - absorption coefficient

  8. Scattering As a photon travels, free path distance direction of its propagation is changed as - scattering angle, where - azimuthal scattering angle, - directional cosines.

  9. Voxel boundary intersection Voxel – photon packet intersection calculated using Smith algorithm: - distances to voxel boundary plane, - current photon location , - Voxel facet length, Distances are compared, and the minimal value represents the distance to the closest voxel boundary.

  10. Photon detection When photon exits tissue its weight added to intensity of the image according to - structural image pixel intensity - wave length - coherence length - fiber acceptance angle - detector radius - distance from center of detector to point where photon exits tissue - Photon path length in object arm

  11. Subcutaneous vessel structure Object structure used in simulation Experimental subcutaneous blood vessel image

  12. Optical properties of the layers

  13. MC simulated images Simulated images of subcutaneous blood vessel with (right) and without (left) speckle influence. Correlation with experimental data is between 0.85 and 0.9 Size of the image is 2x2 mm in all cases

  14. A-scans comparison The biggest difference located at the stratum corneum – air boundary

  15. Conclusion Described simulation technique allows to simulate OCT of biological object with high precision. This is because the structure of an object is reconstructed using information taken from experimental data. High efficiency is provided both for simulation with and without presence of speckles. Some inconsistency may occur due to choose of inaccurate optical properties of the simulated object. Future work will be focused on other types of tissues and light source properties.

  16. References • Kirillin M., Meglinski I., Kuzmin V., Sergeeva E., Myllylä R. Opt. Express, 18(21), P. 21714 (2010). 2. Proskurin S.G., Quantum Electronics, 42 (6), P. 495-499 (2012). http://iopscience.iop.org/1063-7818/42/6/A05/ • Petrov D.A.  Galeb K.E.S.  Proskurin S.G., Fundamental Research,5(2), P. 275-278 (2016) http://fundamental-research.ru/ru/article/view?id=40288 • PetrovD.A., AbdulkareemS.N., GhalebK.E.S., ProskurinS.G., Journal of Biomedical Photonics & Engineering, 2(2) – P. 020302-1 (2016) http://journals.ssau.ru/index.php/JBPE/article/view/2363 • Proskurin S.G., Potlov A.Yu., Frolov S.V., Patent, RU 147284 U1 (2014) • Potlov A.Yu., Proskurin S.G., Frolov S.V., Registered Software, 2014662539 (2014)

More Related