A numerical simulation of photothermal response in laser medicine

In this paper, we reported a numerical solution of laser induced thermal effect in the bio-tissue. The model of photothermal effect and classical Pennes bio-heat transfer equation were introduced. Finite element method (FEM), which was realized by Matlab software, was used to calculate the temperature distribution. He-Ne laser (633 nm) was used to simulate the physical therapy in in vivo skin tissue. Under the cylinder coordinates, the three-dimension(3-D) geometry of tissue was reduced to two-dimension(2-D)computation. The results contained the radial, axial and temperature 3-D color plot. Combining the time animation display was possible. By changing the laser and tissue parameters we can get different results.This will be the initial and indispensable work of the non-destructive evaluation of the laser induced injury.     

A numerical simulation of photothermal response in laser medicine

In this paper, we reported a numerical solution of laser induced thermal effect in the bio-tissue. The model of photothermal effect and classical Pennes bio-heat transfer equation were introduced. Finite element method (FEM), which was realized by Matlab software, was used to calculate the temperature distribution. He-Ne laser (633 nm) was used to simulate the physical therapy in in vivo skin tissue. Under the cylinder coordinates, the three-dimension(3-D) geometry of tissue was reduced to two-dimension(2-D)     

Rotation-invariant texture analysis using Radon and Fourier transforms

Texture analysis is a basic issue in image processing and computer vision,and how to attain the rotation- invariant texture characterization is a key problem.This paper proposes a rotation-invariant texture analysis technique using Radon and Fourier transforms.This method uses Radon transform to convert rotation to translation,then utilizes Fourier transform and takes the moduli of the Fourier transform of these functions to make the translation invariant.A k-nearest-neighbor rule is employed to classify texture images.The proposed method is robust to additive white noise as a result of summing pixel values to generate projections in the Radon transform step.Experiment results show the feasibility of the proposed method and its robustness to additive white noise.