Yiqing Gao

Limited-angle optical computed tomography algorithms

Optical computed tomography (OCT) is often used for measuring thermophysical parameters. Unfortunately, viewing access in many tomographic experiments, such as in plasma physics, is extremely limited, which leads to a highly undetermined inversion problem. Four major approaches to this problem are compared: a novel algorithm based on maximum entropy (ME), and three traditional algorithms, namely the simultaneous iterative reconstruction technique (SIRT), algebraic reconstruction technique (ART), and multiplicative algebraic reconstruction technique (MART). A novel basis function was adopted to improve the performance of SIRT, ART, and MART. These algorithms were used to reconstruct phantom data with realistic levels of noise from a number of different imaging geometries. The phantoms, the imaging geometries, and the noise were chosen to simulate conditions encountered in typical OCT measurement. In most cases, the ME and MART algorithms give better reconstruction results than the other two algorithms for the situations studied here.

Self-adaptive reconstruction algorithm for emission spectral volume tomography

A novel self-adaptive volume reconstruction technique (SVRT) based on multiobjective optimization is proposed. Its reconstruction results for asymmetrical 3-D single-peak cosine emission coefficient fields are studied with the numerical simulation of a computer. The results show that this algorithm has faster convergences and higher reconstruction precision, and can reconstruct asymmetrical single-peak cosine emission coefficient fields perfectly with only two views. (The average error is 0.18% with no noise data.) In the experiment of argon-arc plasma diagnosis, the 3-D reconstructions of temperature and ionization coefficient fields are fulfilled with this algorithm combined with the spectrum relative-intensity method.

Three-dimensional plasma field reconstruction with multiobjective optimization emission spectral tomography

A novel emission spectral tomography algorithm based on multiobjective optimization is proposed. Its reconstruction results for asymmetrical emission coefficient fields are studied with computer simulation. The results show that this algorithm provides a significant improvement in reconstruction precision and convergence over traditional algorithms and is suitable for real-time reconstruction of an emission-coefficient field with incomplete data. In an experiment of the argon-arc plasma diagnosis, we adopted this algorithm and the spectrum relative-intensity method to obtain the three-dimensional distributions of temperature, ionization coefficient, and electron (ion) and atom densities.

Study of Limited-view Tomography Algorithms for Plasma Diagnostics

Optical Computed Tomography is a useful tool for plasma diagnostics. But in plasma physics, viewing access is very limited, which leads a highly undetermined inversion problem. Two major approaches to this problem are compared in this paper: Maximum Entropy (ME) method and Simultaneous Iterative Reconstruction Technique (SIRT). The results of numerical simulation and experiments illustrate that both two algorithms can yield good qualities of reconstruction with limited views when some prior information has incorporated into calculation. Especially, in the case of two views, with prior information, a good result can even be achieved by ME algorithm.

Cancer cell recognition with hybrid optical neural network

In this paper, we consider a promising method of pattern recognition based on Texture Features (TF) to classify cancer cell. With this technique, the TF characters are calculated among different cells or different regions of cells. Then these texture features are transmitted to the input neurons of the Back Propagation (BP) neural network. After training phase of neural network, the structure is determined. At last, we design an opto-electronic neural network to complete the cancer cells recognition.

Large electric current real-time control system based on a wavelength division multiplexing optical fiber network

In the testing and control of electricity system, Magnetism-photo optical fiber electricity sensor modules based on Faraday Effect of the main electricity wire can be made. We can play these sensor modules at the spots where the electricity need to be tested and controlled real-timely and make use of the Wavelength Division Multiplexing (WDM) technique of optical fiber network to transmit the real time data from all spots to the central computer, so the system of distributed optical fiber electricity current supervision and control is constructed.