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Proceedings Paper

Structural analysis and coding of multimodal medical images
Author(s): Olivier Baudin; Atilla M. Baskurt; Florent Dupont; Remy Prost; Robert Goutte; Mohammed Khamadja
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Paper 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.

Paper Details

Date Published: 30 June 1993
PDF: 9 pages
Proc. SPIE 1897, Medical Imaging 1993: Image Capture, Formatting, and Display, (30 June 1993); doi: 10.1117/12.146979
Show Author Affiliations
Olivier Baudin, Institute National des Sciences Appliquees de Lyon (France)
Atilla M. Baskurt, Institute National des Sciences Appliquees de Lyon (France)
Florent Dupont, Institute National des Sciences Appliquees de Lyon (France)
Remy Prost, Institute National des Sciences Appliquees de Lyon (France)
Robert Goutte, Institute National des Sciences Appliquees de Lyon (France)
Mohammed Khamadja, Univ. of Constantine (Algeria)


Published in SPIE Proceedings Vol. 1897:
Medical Imaging 1993: Image Capture, Formatting, and Display
Yongmin Kim, Editor(s)

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