Abstract

The paper presents a hierarchical coding algorithm for 3D medical images based upon hierarchical interpolation with radial basis function networks. By using the properties of the Kronecker product, the computation of the network parameters and the 3D image reconstruction are efficiently done in (L4) computation time and O(L3) storage space, when applied to 3D images of size (L x L x L). A further reduction in 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 reconstruction of 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 18 x 64) and with 8-bit grey levels, show that the coding performance is better than that of the 3D DCT coding by about 0.25 bits pixel-1 at higher bit rates, and that the new cross-section display method synthesises the coarsest (finest) section image about six (three) times faster than the standard method that requires the whole 3D image reconstruction.

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