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Proceedings Paper

Knowledge-based automated technique for measuring total lung volume from CT
Author(s): Matthew S. Brown; Michael F. McNitt-Gray; Nicholas J. Mankovich; Jonathan G. Goldin; Denise R. Aberle
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Paper Abstract

A robust, automated technique has been developed for estimating total lung volumes from chest computed tomography (CT) images. The technique includes a method for segmenting major chest anatomy. A knowledge-based approach automates the calculation of separate volumes of the whole thorax, lungs, and central tracheo-bronchial tree from volumetric CT data sets. A simple, explicit 3D model describes properties such as shape, topology and X-ray attenuation, of the relevant anatomy, which constrain the segmentation of these anatomic structures. Total lung volume is estimated as the sum of the right and left lungs and excludes the central airways. The method requires no operator intervention. In preliminary testing, the system was applied to image data from two healthy subjects and four patients with emphysema who underwent both helical CT and pulmonary function tests. To obtain single breath-hold scans, the healthy subjects were scanned with a collimation of 5 mm and a pitch of 1.5, while the emphysema patients were scanned with collimation of 10 mm at a pitch of 2.0. CT data were reconstructed as contiguous image sets. Automatically calculated volumes were consistent with body plethysmography results (< 10% difference).

Paper Details

Date Published: 8 April 1996
PDF: 12 pages
Proc. SPIE 2709, Medical Imaging 1996: Physiology and Function from Multidimensional Images, (8 April 1996);
Show Author Affiliations
Matthew S. Brown, Univ. of New South Wales and CSIRO (Australia)
Michael F. McNitt-Gray, UCLA School of Medicine (United States)
Nicholas J. Mankovich, UCLA School of Medicine (United States)
Jonathan G. Goldin, UCLA School of Medicine (United States)
Denise R. Aberle, UCLA School of Medicine (United States)

Published in SPIE Proceedings Vol. 2709:
Medical Imaging 1996: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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