基于矢量场自适应采样算法的图像体绘制技术

针对医学数据体绘制的特点，研究了体数据矢量场的变化特征，分析了采样频率与矢量场的关系，提出基于矢量场的自适应采样算法，对重建图像贡献最大的数据区域采用高频采样，对其贡献小的数据区域采用低频采样，从而自适应地控制采样步长，提高了重建性能.研究结果表明，自适应采样算法在重建效果不受影响的前提下，将重建速度提高约30％～60％.

An Adaptive Sampling Algorithm Based on Vector Field for Medical Volume Rendering

Aiming at the characteristic of medical volume rendering, this article studied the variety of vector field of data, analyzed the relationship between the grads vector field of the medical volume data set and the sampling frequency, then proposed an adaptive sampling algorithm, in which the volume area that is more to contribute to the final image would be sampled with high frequency, and in a relative manner, the volume area that is less to contribute to the final image would be sampled with low frequency. In this way, the sampling step is adjusted adaptively, and the performance of volume reconstruction is improved. The experiments show that the performance of the volume reconstruction is improved by about 30%~60%, while the quality of image is ensured.