Catalin Fetita

TL;DR: A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

TL;DR: Improve in image analysis technique and the use of spirometrically control of lung volume acquisition have made possible accurate and reproducible quantitative assessment of airway wall and lumen areas and lung density, which contributes to better insights in physiopathology of obstructive lung disease, particularly in chronic obstructive pulmonary disease and asthma.

TL;DR: An annotated reference dataset is presented and a quantitative scoring system is proposed for objective comparison of algorithms and performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.

TL;DR: The proposed functionality relies on an energy-based three-dimensional reconstruction of the bronchial tree from multislice CT acquisitions, up to the sixth- to seventh-order subdivisions, and proved to be robust with respect to a large spectrum of airway pathologies, including even severe stenosis.

TL;DR: A new approach of bronchi segmentation in HRCT in order to estimate the bronchial caliber is addressed, and it is shown that, according to the size of the bronchi, the estimation accuracy is up to 90%.