As with many other techniques, what is described here works on vector-valued volume data, in which each material has a characteristic vector value rather than a characteristic scalar value. Vector-valued datasets have a number of advantages and generally give better classification results. Such datasets have improved SNR and frequently distinguish similar materials more effectively (see Fig. 13).
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