研究目的
The aim of the work is to develop a method for numerical simulation of the OCT image formation process. The developed method will takes into account complex optical structure of real biological tissues and the presence of speckle noise.
研究成果
The algorithm and Monte-Carlo software for simulating OCT signals with consideration of speckle fluctuations are presented, validated by high correlation coefficients (0.85-0.95) with experimental images. The method can be used for numerical experiments to study low-coherence radiation propagation in scattering media and for obtaining high-quality endoscopic OCT images.
研究不足
The method may have limitations in handling highly complex or dynamic biological tissues, and the simulation accuracy depends on the number of photons and A-scans used (e.g., 10 million photons per A-scan and 180 A-scans in the example).
1：Experimental Design and Method Selection:
The method uses Monte Carlo simulation for low-coherence radiation propagation in turbid media, incorporating speckle noise. It involves steps such as photon injection, mean free path determination, boundary condition verification, absorption, and scattering. An improved Smith algorithm is used for border cross checking in a voxel-based geometry model.
2：Sample Selection and Data Sources:
The simulation is applied to biological tissues, specifically human skin containing a blood vessel in vivo, using posterization of original images to fragment structures and assign optical parameters.
3：List of Experimental Equipment and Materials:
No specific equipment or materials are listed; the method is implemented as a software package in LabVIEW.
4：Experimental Procedures and Operational Workflow:
Photons are launched from sources (point, Gaussian, or collimated Gaussian beam), their paths are calculated with scattering and absorption, boundary conditions are checked using the Smith algorithm, and statistical weights are summed for image reconstruction.
5：Data Analysis Methods:
The correlation coefficient between experimental and simulated images is calculated to validate the method.
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