Compression of 3D MRI image data based upon regularization theory and the fast cross section display

提出了一种基于径向基函数网络分层插值的三维医学图像分层编码算法。利用Kronecker积的性质，当应用于大小为（LxLxL）的三维图像时，网络参数的计算和三维图像的重建在O（L^4）的计算时间和O（L^3）的存储空间内有效地完成。进一步减少处理时间是通过使用稀疏矩阵技术。该编码方法的显著特点是：不需要重建整个三维图像就可以渐进地显示任意截面的图像，第一次图像重建在第一次数据传输完成后立即开始，三维图像重建不需要扩展过程，即使在最低分辨率的图像中块效应也不明显。实验结果使用两个3D MRI图像的大小（128 × 128 × 64）显示编码性能比3D DOT编码在较高比特率时好约0.25比特/像素，新的截面显示方法合成了六（三）个左右的粗（细）截面图像，比需要整个3D图像重建的标准方法快一倍。

A hierarchical coding algorithm for 3D medical images based upon hierarchical interpolation with radial basis function networks is proposed. By using the properties of Kronecker product, the computation of the network parameters and the 3D image reconstruction are efficiently done in O(L^4) computation time and O(L^3) storage space, when applied to 3D images of size (L x L x L). A further reduction of processing time is accomplished by using sparse matrix techniques. The salient features of the proposed coding method are that arbitrary cross section images can be progressively displayed without reconstructing the whole 3D image, the first image reconstruction starts as soon as the first data transmission has been completed, no expanding procedure is required in 3D image reconstruction, and the blocking effects are not apparent even in the lowest resolution image. Experimental results using two 3D MRI images of size (128 x 128 x 64) with 8-bit gray levels show that the coding performance is better than that of the 3D DOT coding by about 0.25 bits/pixel at higher bitrates, and that the new cross section display method synthesizes the coarsest (finest) section image about six (three) times faster than the standard method that requires the whole 3D image reconstruction.