基于改进MC算法和分数阶混沌的CT图像三维重建和加密方案

在现代医疗领域的病理诊断与手术实操中，需要对CT进行三维重建实现二维图像的三维可视化以提高诊断和操作的正确性。针对目前三维重建耗时过长、精度欠佳等问题，提出了一种改进的MC算法，采用包围盒分割算法提取包含等值面的体素，有效提高了重建效率；利用三线性插值法计算等值面与体素的交点信息，从而提高了重建精度。为保障医疗信息在云存储以及网络传输的安全性，提出了一种基于分数阶Lorenz混沌的三维模型加密方案，实现了重建数据在频域的混沌加密。实验结果表明，改进的MC算法具有良好的重建效率和重建精度，提出的加密方案能有效地保护重建后的三维数据，并能抵抗穷举攻击、差分攻击和统计攻击。

3D reconstruction and encryption scheme of CT images based on improved MC algorithm and fractional-order chaos

In the modern medical field of pathological diagnosis and surgical practice, it is necessary to perform three-dimensional reconstruction of CT(computed tomography) to realize three-dimensional visualization of two-dimensional images to improve the accuracy of diagnosis and operation. To address the current problems of time-consuming and poor accuracy of 3D reconstruction, this paper proposed an improved MC(marching cubes) algorithm, which used an enclosing box segmentation algorithm to extract voxels containing equivalent surfaces, effectively improving the reconstruction efficiency, calculated the intersection of equivalent surfaces and voxels by using trilinear interpolation, thus improving the reconstruction accuracy. In order to ensure the security of medical information in cloud storage and network transmission, this paper proposed a threedimensional model encryption scheme based on fractional Lorenz chaos, which realized the chaotic encryption of reconstruction data in the frequency domain. The experimental results show that the improved MC algorithm has good reconstruction efficiency and reconstruction accuracy, and the proposed encryption scheme can effectively protect the reconstructed 3D data and resist exhaustive attacks, differential attacks and statistical attacks.