Paper
23 February 2012 Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach
C Fetita, K. C. Chang-Chien, P. Y. Brillet, F. Prêteux, R. F. Chang
Author Affiliations +
Abstract
Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.
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C Fetita, K. C. Chang-Chien, P. Y. Brillet, F. Prêteux, and R. F. Chang "Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83152Z (23 February 2012); https://doi.org/10.1117/12.911350
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KEYWORDS
Lung

Image classification

Emphysema

Tissues

CAD systems

Classification systems

Computed tomography

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