| 1. |
- Friman, Ola, 1975-, et al.
(author)
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Recognizing emphysema - A neural network approach
- 2002
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In: Pattern Recognition, 2002. Proceedings. 16th International Conference on (Volume:1). - : IEEE Computer Society. ; , s. 512-515
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Conference paper (peer-reviewed)abstract
- An accurate and fully automatic method for detecting and quantifying emphysema in CT-images is presented. The method is based on an image preprocessing step followed by a neural network classifier trained to separate true emphysema from artifacts. The proposed approach is shown to be superior to an established method when applied on real patient data.
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| 2. |
- Tylén, Ulf, et al.
(author)
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An improved algorithm for computerized detection and quantification of pulmonary emphysema at high resolution computed tomography (HRCT)
- 2001
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In: SPIE01,2001. - : SPIE. ; , s. 254-262
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Conference paper (peer-reviewed)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.
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| 3. |
- Vikgren, Jenny, 1957, et al.
(author)
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Detection of mild emphysema by computed tomography density measurements
- 2005
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In: Acta Radiologica. - : SAGE Publications. - 0284-1851 .- 1600-0455. ; 46:3, s. 237-245
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Journal article (peer-reviewed)abstract
- Purpose: To assess the ability of a conventional density mask method to detect mild emphysema by high- resolution computed tomography ( HRCT), to analyze factors influencing quantification of mild emphysema, and to validate a new algorithm for detection of mild emphysema. Material and Methods: Fifty- five healthy male smokers and 34 never- smokers, 61 - 62 years of age, were examined. Emphysema was evaluated visually, by the conventional density mask method, and by a new algorithm compensating for the effects of gravity and artifacts due to motion and the reconstruction algorithm. Effects of the reconstruction algorithm, slice thickness, and various threshold levels on the outcome of the density mask area were evaluated. Results: Forty- nine percent of the smokers had mild emphysema. The density mask area was higher the thinner the slice irrespective of the reconstruction algorithm and threshold level. The sharp algorithm resulted in increased density mask area. The new reconstruction algorithm could discriminate between smokers with and those without mild emphysema, whereas the density mask method could not. The diagnostic ability of the new algorithm was dependent on lung level. At about 90% specificity, sensitivity was 65 - 100% in the apical levels, but low in the rest of the lung. Conclusion: The conventional density mask method is inadequate for detecting mild emphysema, while the new algorithm improves the diagnostic ability but is nevertheless still imperfect.
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