体数据中边界点计算的新方法

为了提高三维重构的精度,分析了Marching Cubes方法所产生的误差,提出获得边界点的新方法.新方法依据阈值区分出边界内、边界外和边界像素,利用这3个像素的像素值来决定边界点的位置.并且针对边界点的位置,提出了三角形网格结构的调整方法.理论分析表明, 当边界在像素级别上是直线段时,新方法能够直接计算出精确的边界点.区分等值点和边界点,基于边界点,给出了不同于MC方法的等值点计算方法.最后用CT数据实例比较了新方法和MC方法.

A New Method to Find the Boundary Point from Volume Data

It is important to improve the precision of the reconstructed surfaces from volume data.The marching cubes method and its precision are analyzed in detail.It is found that the error brought by the marching cubes method can reach to 1.5 pixels,which is a serious problem for reconstructing the small and thin objects,such as human blood vessels.A new method with more precision is presented.The new method distinguishes the pixels inside,across or outside of the boundary by a threshold,and determines the position of the boundary point according to the values of the three adjacent pixels(inside,across and outside),which is different from the marching cubes.The new method also modifies the grid topology of the MC method,considering the position change of boundary points.Theoretical analysis shows that the new method can find the accurate boundary points when the boundary is a straight line in a pixel.The precision and overhead of the new method are discussed.Finally examples of CT data show the contrast between the new method and the MC method.