Bede Liu

Interframe coding of magnetic resonance images

Presents a new interframe coding method for medical images, in particular magnetic resonance (MR) images. Until now, attempts in using interframe redundancies for coding MR images have been unsuccessful. The authors believe that the main reason for this is twofold: unsuitable interframe estimation models and the thermal noise inherent in magnetic resonance imaging (MRI). The interframe model used here is a continuous affine mapping based on (and optimized by) deforming triangles. The inherent noise of MRI is dealt with by using a median filter within the estimation loop. The residue frames are quantized with a zero-tree wavelet coder, which includes arithmetic entropy coding. This particular method of quantization allows for progressive transmission, which aside from avoiding buffer control problems is very attractive in medical imaging applications.

Adaptive entropy coded DCT coding of magnetic resonance image sequences

Compression of magnetic resonance (MR) image sequences have proved to be difficult as compared to other medical imaging modalities. Some of the factors partially responsible for this are significant amount of noise and image artifacts which are present in a 3-D MR dataset. Another factor is use of unsuitable intensity matching techniques in removal of inter-slice dependencies. In this paper we introduce an adaptive DCT coding scheme that employs a triangle-based matching (TBM) algorithm to explore the inter-slice dependencies. The proposed scheme is used to encode a heart sequence. An improvement of 0.3 dB is achieved over adaptive intra-slice schemes at low bit-rates.<<ETX>>