A novel method combining the PCA-NN algorithm established on the single-layer tissue model and the genetic algorithm based on the two-layer diffusion model has been presented to determine the optical properties of the two-layer medium from the steady-state spatially resolved diffuse reflectance. In detail, we firstly employ the PCA-NN algorithm established on the semi-infinite tissue model to extract the optical properties of the top layer from the spatially resolved reflectance that results from the photons migrating mainly within the top layer. With the knowledge of the optical properties of the top layer, the optical properties of the bottom layer are then obtained by use of the genetic algorithm for fitting the two-layer diffusion model to the reflectance data far from the source. The method was validated using the Monte Carlo generated reflectance for the two-layer medium of skin overlying fat or skin overlying muscle. And, the skin thickness was assumed to be known a priori and fixed at 5 mm. The results showed that all the optical properties of two layers can be determined by the method with the accuracy of better than 10%.
In this paper, with reference to practical applications, we investigate the accuracy of the PCA-NN method in determining the optical properties μa and μs' from the spatially resolved relative reflectance data produced by Monte Carlo simulations. To test prediction performance of PCA-NN from the reflectance data with different lengths and different measurement noises, we constructed six PCA-NNs respectively corresponding to data length = 5, 10, 15, 20, 25 and 30 mm, which were trained by higher precision reflectance produced with photons = 107. Then lower precision reflectance generated with photons = 104, 2 × 104, 5 × 104, 7 × 104, 105, 2 × 105, 5 × 105, 7 × 105 and 106 were inputted to PCA-NNs to extract μa and μs' and the accuracy of μa and μs' was calculated, respectively. The results showed that for the reflectance with the same data length, the prediction errors of μa and μs' increase as the data noise increases; but for the reflectance with the same data precision, the errors decrease as the data length becomes longer. In conclusion, the preliminary results in this paper provide a guideline for choosing appropriate measurement conditions or estimating the prediction errors in reality.
As a numerical experiment, Monte Carlo simulation (MCS) has been proven to be a credible and flexible method for predicting the distribution of light in random media. It has full control of many parameters of optical system, which may be cumbersome to obtain in a real experiment. In standard OCT system, confocal microscopy structure with different Numerical Aperture (NA) is selected to acquire superior transverse resolution and unique property of optical sectioning. But the effects of numerical aperture on the probing depth of OCT system are difficult to estimate. In this paper, a new Monte Carlo simulation model of OCT system based on confocal mode is put forward to simulate the confocal microscopy structure and focused gaussian beam. It makes up the deficiency of traditional MCS model, which can only be applied to infinity narrow beam. By applying this new model, the effects of NA on probing depth of OCT system are analyzed, and the estimation of critical probing depth of OCT system is discussed. Study indicates that a smaller numerical aperture has more advantage on the probing depth when the transverse resolution is ensured.
Optical coherence tomography (OCT) is a new biomedical imaging technique in resent year. It has some good qualities, such as non-ionizing radiation, non-invasive, high resolution and sensitivity. High-speed OCT imaging is very important for obtaining the cross-sectional images of the internal microstructure of living tissue. Increasing the imaging speed can produce imaging real time. To study high speed OCT, a new method of OCT imaging technique has been designed in this paper--replacing the point-focus mode with line-focus mode in the sample arm. Cylindrical lens can be used for focusing the incident light into a line in the sample. And a 2D OCT imaging can be obtained in one dimension scanning. In the paper we analyze the interference principle of line-focus imaging mode.
Optical coherence tomography (OCT) based on the theory of Michelson interferometer is a novel imaging technique with high resolution and performs non-invasive. The images of traditional OCT system can be obtained through pointscanning which its scanning speed is slow, and this limits the real time measurement of the system. This paper introduces a new imaging technique of OCT system with high speed, using line-scanning method instead of pointscanning method. The new method can increase the scanning speed and can realize real time measurement, which provide a fundamental technique for the high-speed imaging.
KEYWORDS: Digital signal processing, Optical coherence tomography, Data acquisition, Signal processing, Imaging systems, Tissues, Data processing, Demodulation, Modulators, Image processing
Optical Coherence Tomography (OCT) is a novel optical imaging technology that provides high-resolution cross-sectional views of subsurface microstructure of biological tissues. It features high sensitivity, noninvasiveness, high resolution of micron scale, probing depth of 2cm for transparent tissue and 1~2mm for highly scattering tissue, and etc. OCT has shown a promising future to become a complement to the conventional imaging techniques in the fields of medicine and biology. But there are still a number of problems should be solved before OCT technology can be applied to practical usage. One of those is the limited imaging speed. In this paper, a high-speed data acquisition and processing (DAP) system for OCT is presented. Built around the high-powered Digital signal Processor (DSP) TMS32OVC5410A, the system is designed to cooperate with a PC to realize the image-scanning control, signal acquisition, data processing, transmission, image reconstruction and display. Superior to conventional data acquisition systems (DAQs), this system implants pre-processing of raw data into DSP, thus reduces the image acquisition time by carrying out the large amount of computation in the DSP, rather than in the PC. In addition, it can present two images with different information at per 2-D scans. And the system can be extended to future diverse applications by loading flexible digital signal processing schemes.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.