一种可调整步长的适应性图像目标轮廓采样方法

为了更有效地获得三维医学图像，提出了一种可调整步长的适应性图像目标轮廓采样方法。直接获取自临床的层阃间距相对较大的医学图像数据，首先经由图像预处理和图像目标轮廓插值等前期数据预处理操作，然后采用本文提出的一种可调整步长的适应性图像目标轮廓采样方法对图像目标轮廓线上的点进行适应性采样，最后给出了图像目标的三雏表面显示效果图。实验结果证实了方法的可靠性和有效性。该采样方法既保持了图像目标轮廓的尖锐特征和拓扑结构，又较好地实现了数据压缩。

Adaptive Step-Variable Sampling Method for Image Object Contour

To research three-dimension medical images more effectively, an adaptive step-variable sampling method for image object contour is proposed. Firstly the object contours on the images are preprocessed and interploated, and the images are directly acquired from clinical practice and are spaced relatively sparse. Then the proposed step-variable contour sampling method is used to adaptively sample the processed contours. Finally, the 3D rendering for the image object is given. Theoretical and experimental results indicate that the method is reliable and valid. Results prove that the sampling method can maintain the acute characters and topology of the object contours on the images and attain the aim of data compression.