Nader Mohsenian

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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(More)
Most real-time MPEG-2 encoders are designed to perform in a constant-bit-rate (CBR) mode, in which buffer constraints are imposed to circumvent large deviations from a desired rate at any instant in time. Although such streams are generally good-quality sequences, certain types of operations or environments call for a more efficient real-time CBR encoder.(More)
Compression of magnetic resonance images (MRI) has proved to be more diicult than other medical imaging modalities, and attempts at utilizing inter-slice dependencies for more eecient coding have so far met with little success. On the other hand, the increasing amounts of MRI data generated every day in hospitals makes this particular data compression(More)
A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. The SVQ is a fixed rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity(More)
A predictive vector quantization scheme exploiting the intervector correlations of adjacent blocks (vectors) of pixels is developed. The model presented utilizes the statistical dependencies of the previously encoded pairs of adjacent blocks to predict future blocks of picture elements. The state of the vector predictor is represented by a subcodebook(More)
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