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30 June 1993 Structural analysis and coding of multimodal medical images
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An adaptive image coding scheme based on Discrete Cosine Transform (DCT) is considered. A set of 90 features in the spatial and spectral domain leads to a subset of features which is used to automatically classify subimages, taken from a multimodal medical image data base. The classifier, based on a binary decision tree, discriminates 13 classes. In the DCT domain, a normalization matrix for each class is generated using the features computed on subimages. This matrix allows to select the significant DCT coefficients associated to a class. This method leads to a performant adaptativity for the coding scheme. The classifier is very simple and cheap in computing time. A given subimage is classified, transformed with DCT, normalized by the matrix associated to its class, quantized and coded with Huffman tables.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olivier Baudin, Atilla M. Baskurt, Florent Dupont, Remy Prost, Robert Goutte, and Mohammed Khamadja "Structural analysis and coding of multimodal medical images", Proc. SPIE 1897, Medical Imaging 1993: Image Capture, Formatting, and Display, (30 June 1993);

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