30 June 1993 Structural analysis and coding of multimodal medical images
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Abstract
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.
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Olivier Baudin, Olivier Baudin, Atilla M. Baskurt, Atilla M. Baskurt, Florent Dupont, Florent Dupont, Remy Prost, Remy Prost, Robert Goutte, Robert Goutte, Mohammed Khamadja, Mohammed Khamadja, } "Structural analysis and coding of multimodal medical images", Proc. SPIE 1897, Medical Imaging 1993: Image Capture, Formatting, and Display, (30 June 1993); doi: 10.1117/12.146979; https://doi.org/10.1117/12.146979
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