Paper
21 May 2001 Improved algorithm for computerized detection and quantification of pulmonary emphysema at high-resolution computed tomography (HRCT)
Ulf Tylen, Ola Friman, Magnus Borga, Jan-Erik Angelhed
Author Affiliations +
Abstract
Emphysema is characterized by destruction of lung tissue with development of small or large holes within the lung. These areas will have Hounsfield values (HU) approaching -1000. It is possible to detect and quantificate such areas using simple density mask technique. The edge enhancement reconstruction algorithm, gravity and motion of the heart and vessels during scanning causes artefacts, however. The purpose of our work was to construct an algorithm that detects such image artefacts and corrects them. The first step is to apply inverse filtering to the image removing much of the effect of the edge enhancement reconstruction algorithm. The next step implies computation of the antero-posterior density gradient caused by gravity and correction for that. Motion artefacts are in a third step corrected for by use of normalized averaging, thresholding and region growing. Twenty healthy volunteers were investigated, 10 with slight emphysema and 10 without. Using simple density mask technique it was not possible to separate persons with disease from those without. Our algorithm improved separation of the two groups considerably. Our algorithm needs further refinement, but may form a basis for further development of methods for computerized diagnosis and quantification of emphysema by HRCT.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ulf Tylen, Ola Friman, Magnus Borga, and Jan-Erik Angelhed "Improved algorithm for computerized detection and quantification of pulmonary emphysema at high-resolution computed tomography (HRCT)", Proc. SPIE 4321, Medical Imaging 2001: Physiology and Function from Multidimensional Images, (21 May 2001); https://doi.org/10.1117/12.428144
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Cited by 5 scholarly publications.
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KEYWORDS
Emphysema

Lung

Tissues

Reconstruction algorithms

Algorithm development

Computed tomography

Image filtering

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