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Proceedings Paper

Robust lung identification in MSCT via controlled flooding and shape constraints: dealing with anatomical and pathological specificity
Author(s): Catalin Fetita; Sebastian Tarando; Pierre-Yves Brillet; Philippe A. Grenier
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Paper Abstract

Correct segmentation and labeling of lungs in thorax MSCT is a requirement in pulmonary/respiratory disease analysis as a basis for further processing or direct quantitative measures: lung texture classification, respiratory functional simulations, intrapulmonary vascular remodeling evaluation, detection of pleural effusion or subpleural opacities, are only few clinical applications related to this requirement. Whereas lung segmentation appears trivial for normal anatomo-pathological conditions, the presence of disease may complicate this task for fully-automated algorithms. The challenges come either from regional changes of lung texture opacity or from complex anatomic configurations (e.g., thin septum between lungs making difficult proper lung separation). They make difficult or even impossible the use of classic algorithms based on adaptive thresholding, 3-D connected component analysis and shape regularization. The objective of this work is to provide a robust segmentation approach of the pulmonary field, with individualized labeling of the lungs, able to overcome the mentioned limitations. The proposed approach relies on 3-D mathematical morphology and exploits the concept of controlled relief flooding (to identify contrasted lung areas) together with patient-specific shape properties for peripheral dense tissue detection. Tested on a database of 40 MSCT of pathological lungs, the proposed approach showed correct identification of lung areas with high sensitivity and specificity in locating peripheral dense opacities.

Paper Details

Date Published: 29 March 2016
PDF: 10 pages
Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97881A (29 March 2016); doi: 10.1117/12.2216687
Show Author Affiliations
Catalin Fetita, Télécom SudParis, Institut Mines-Telecom (France)
MAP5, CNRS (France)
Sebastian Tarando, Télécom SudParis, Institut Mines-Telecom (France)
Pierre-Yves Brillet, Univ. Paris 13 (France)
Philippe A. Grenier, Univ. Paris 6 (France)

Published in SPIE Proceedings Vol. 9788:
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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