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Proceedings Paper

Automated diagnosis of interstitial lung diseases and emphysema in MDCT imaging
Author(s): Catalin Fetita; Kuang-Che Chang Chien; Pierre-Yves Brillet; Françoise Prêteux
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Paper Abstract

Diffuse lung diseases (DLD) include a heterogeneous group of non-neoplasic disease resulting from damage to the lung parenchyma by varying patterns of inflammation. Characterization and quantification of DLD severity using MDCT, mainly in interstitial lung diseases and emphysema, is an important issue in clinical research for the evaluation of new therapies. This paper develops a 3D automated approach for detection and diagnosis of diffuse lung diseases such as fibrosis/honeycombing, ground glass and emphysema. The proposed methodology combines multi-resolution 3D morphological filtering (exploiting the sup-constrained connection cost operator) and graph-based classification for a full characterization of the parenchymal tissue. The morphological filtering performs a multi-level segmentation of the low- and medium-attenuated lung regions as well as their classification with respect to a granularity criterion (multi-resolution analysis). The original intensity range of the CT data volume is thus reduced in the segmented data to a number of levels equal to the resolution depth used (generally ten levels). The specificity of such morphological filtering is to extract tissue patterns locally contrasting with their neighborhood and of size inferior to the resolution depth, while preserving their original shape. A multi-valued hierarchical graph describing the segmentation result is built-up according to the resolution level and the adjacency of the different segmented components. The graph nodes are then enriched with the textural information carried out by their associated components. A graph analysis-reorganization based on the nodes attributes delivers the final classification of the lung parenchyma in normal and ILD/emphysematous regions. It also makes possible to discriminate between different types, or development stages, among the same class of diseases.

Paper Details

Date Published: 17 September 2007
PDF: 12 pages
Proc. SPIE 6700, Mathematics of Data/Image Pattern Recognition, Compression, Coding, and Encryption X, with Applications, 67000G (17 September 2007); doi: 10.1117/12.734147
Show Author Affiliations
Catalin Fetita, ARTEMIS, Institut National des Télécommunications (France)
Kuang-Che Chang Chien, ARTEMIS, Institut National des Télécommunications (France)
National Chung Cheng Univ. (Taiwan)
Pierre-Yves Brillet, ARTEMIS, Institut National des Télécommunications (France)
Avicenne Hospital (France)
Françoise Prêteux, ARTEMIS, Institut National des Télécommunications (France)


Published in SPIE Proceedings Vol. 6700:
Mathematics of Data/Image Pattern Recognition, Compression, Coding, and Encryption X, with Applications
Gerhard X. Ritter; Mark S. Schmalz; Junior Barrera; Jaakko T. Astola, Editor(s)

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