基于反距离加权插值和改进采样点数据合成的医学影像三维重建

传统的体绘制光线投射算法虽然已成为医学影像三维重建的主流方法之一，但是其生成的三维模型质量与绘制速度仍不能满足临床医学诊断的要求。本研究提出一种基于反距离加权插值和改进采样点数据合成的医学影像三维重建算法，通过反距离加权插值方法提升绘制速度；通过增加采样点的个数提高三维重建的成像质量。实验结果表明，该算法在提高成像质量的同时可以提高绘制速度，可将圆锥绘制速度较传统方法提升20％，髋关节平均绘制速度提升18％，并且生成圆锥图像的MSE小于传统算法，SSIM大于传统算法。

Three-dimensional medical image reconstruction using inverse distance weight and improved data synthesis of sampling points

Abstract: Although the traditional volume rendering algorithm using ray casting has become one of the mainstream methods for three-dimensional (3D) image reconstruction in medical imaging, the imaging quality and rendering speed still cannot meet the requirements for clinical medical diagnosis. A 3D image reconstruction algorithm using inverse distance weight and improved data synthesis of sampling points is proposed, with inverse distance weight to reduce the rendering time, and increasing number of sampling points to enhance the imaging quality of 3D image reconstruction. The experimental results reveal that the proposed algorithm can enhance the rendering speed while improving imaging quality. Compared with the traditional method, the 3D image reconstruction algorithm using inverse distance weight and improved data synthesis of sampling points increases the conical rendering speed by 20%, enhances the hip joint rendering speed by 18%, and has smaller MSE and higher SSIM in conical image reconstruction.