Conference proceeding
Effect of mixing scanner types and reconstruction kernels on the characterization of lung parenchymal pathologies: emphysema, interstitial pulmonary fibrosis and normal non-smokers
Proceedings of SPIE, Vol.6143(1), pp.61430M-61430M-9
Medical Imaging 2006: Physiology, Function, and Structure from Medical Images
03/02/2006
DOI: 10.1117/12.657595
Abstract
In this study we utilize our texture characterization software (3-D AMFM) to characterize interstitial lung diseases (including emphysema) based on MDCT generated volumetric data using 3-dimensional texture features. We have sought to test whether the scanner and reconstruction filter (kernel) type affect the classification of lung diseases using the 3-D AMFM. We collected MDCT images in three subject groups: emphysema (n=9), interstitial pulmonary fibrosis (IPF) (n=10), and normal non-smokers (n=9). In each group, images were scanned either on a Siemens Sensation 16 or 64-slice scanner, (B50f or B30 recon. kernel) or a Philips 4-slice scanner (B recon. kernel). A total of 1516 volumes of interest (VOIs; 21x21 pixels in plane) were marked by two chest imaging experts using the Iowa Pulmonary Analysis Software Suite (PASS). We calculated 24 volumetric features. Bayesian methods were used for classification. Images from different scanners/kernels were combined in all possible combinations to test how robust the tissue classification was relative to the differences in image characteristics. We used 10-fold cross validation for testing the result. Sensitivity, specificity and accuracy were calculated. One-way Analysis of Variances (ANOVA) was used to compare the classification result between the various combinations of scanner and reconstruction kernel types. This study yielded a sensitivity of 94%, 91%, 97%, and 93% for emphysema, ground-glass, honeycombing, and normal non-smoker patterns respectively using a mixture of all three subject groups. The specificity for these characterizations was 97%, 99%, 99%, and 98%, respectively. The F test result of ANOVA shows there is no significant difference (p <0.05) between different combinations of data with respect to scanner and convolution kernel type. Since different MDCT and reconstruction kernel types did not show significant differences in regards to the classification result, this study suggests that the 3-D AMFM can be generally introduced.
Details
- Title: Subtitle
- Effect of mixing scanner types and reconstruction kernels on the characterization of lung parenchymal pathologies: emphysema, interstitial pulmonary fibrosis and normal non-smokers
- Creators
- Ye Xu - University of IowaEdwin J van Beek - University of IowaGeoffrey McLennan - University of IowaJunfeng Guo - University of IowaMilan Sonka - University of IowaEric Hoffman - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.6143(1), pp.61430M-61430M-9
- Conference
- Medical Imaging 2006: Physiology, Function, and Structure from Medical Images
- DOI
- 10.1117/12.657595
- ISSN
- 0277-786X
- Language
- English
- Date published
- 03/02/2006
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186593702771
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