Medical Tomography Images Of Rapid Visualization Technology Research And Application

Three-dimensional visualization for medical tomography image is an important application domain in visualization calculation. More and more medical imaging data are obtained from CT medical photograph device, and it is difficult to process so much data in three-dimensional visualization. Therefore, it is important to improve the speed of processing and ensure the image quality. Due to spacing among medical tomography images, ladderlike contour is displayed. Interpolation calculation is an important task in the visualization process for medical tomography image, and it costs a lot of time. Therefore, efficient interpolation algorithm is a key to improve speed for tomography image visualization.This paper analyzed the principle of Ray Casting. A new method of Inverse-Distance Weighting interpolation was proposed for medical tomography image visualization. It aimed at improving the speed of traditional Tri-linear interpolation in the three-dimensional image visualization. After Voxelization for point set in space, weight calculation and interpolation point mapping, Inverse-Distance Weighting was implemented. The experiment results showed that the proposed method was more flexible and less times of operation, then it reduced the number of interpolation and improved the imaging speed. In accordance with the spatial relationships among interpolation points, a fast skipping strategy based on Proximity Clouds algorithm was introduced, and it reduced a lot of invalid interpolation calculation. In the Proximity Clouds algorithm, we studied and designed the distance transformation map,which combines with city block distance metric strategyand eusures that the movement of interpolation point skipps the space area along the ray direction in order to reach the next point. The experiment proved that this method reduced the number of interpolation and improved the imaging speed. We developed visualization Platform for CT tomography image, and Inverse-Distance Weighting and Proximity Clouds algorithms were applied in the Platform, the running result showed that visualization was effective.