Journal article
Quantification of Pulmonary Emphysema from Lung Computed Tomography Images
American journal of respiratory and critical care medicine, Vol.156(1), pp.248-254
07/1997
DOI: 10.1164/ajrccm.156.1.9606093
PMID: 9230756
Abstract
A texture-based adaptive multiple feature method (AMFM) for evaluating pulmonary parenchyma from computed tomography (CT) images is described. This method incorporates multiple statistical and fractal texture features. The AMFM was compared to two previously published methods, namely, mean lung density (MLD) and the lowest fifth percentile of the histogram (HIST). First, the ability of these methods to detect subtle differences in ventral-dorsal lung density gradient in the prone normal lung was studied. Second, their abilities to differentiate between normal and emphysematous whole lung slices were compared. Finally, regional analyses comparing normal and emphysematous regions were performed by dividing the lungs. In the CT slices into six equal regions, ventral to dorsal, and analyzing each region separately. The results demonstrated that the AMFM could separate the ventral from the dorsal one-third of the normal prone lung with 89.8% accuracy, compared to an accuracy of 74.6% with the MLD and 64.4% with the HIST methods. The normal and emphysematous slices were separated on a global basis with 100.0% accuracy using the AMFM as compared to an accuracy of 94.7% and 97.4% using the MLD and HIST methods, respectively. The regional normal and emphysematous tissues were discriminated with an average accuracy of 97.9%, 89.9%, and 99.1% with the AMFM, MLD, and HIST methods, respectively. The three methods and the pulmonary function tests in the normal and emphysema groups were poorly correlated. Quantitative texture analysis using adaptive multiple features holds promise for the objective noninvasive evaluation of the pulmonary parenchyma.
Details
- Title: Subtitle
- Quantification of Pulmonary Emphysema from Lung Computed Tomography Images
- Creators
- RENUKA UPPALURITHEOPHANO MITSAMILAN SONKAERIC A HOFFMANGEOFFREY McLENNAN
- Resource Type
- Journal article
- Publication Details
- American journal of respiratory and critical care medicine, Vol.156(1), pp.248-254
- DOI
- 10.1164/ajrccm.156.1.9606093
- PMID
- 9230756
- NLM abbreviation
- Am J Respir Crit Care Med
- ISSN
- 1073-449X
- eISSN
- 1535-4970
- Language
- English
- Date published
- 07/1997
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984046912002771
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