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A Screening System for the Assessment of Opacity Profusion in Chest Radiographs of Miners with Pneumoconiosis
- Source :
- SSIAI, Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002
- Publication Year :
- 2002
- Publisher :
- Zenodo, 2002.
-
Abstract
- The aim of this study was to develop a screening system of chest radiographs of miners with pneumoconiosis. Chest radiographs were of coal mine or silica dust exposed miners participating in a health screening program. A total of 236 regions of interest (ROI) (166, 49, and 21 with profusions of category (shape and size) 0, 1(q), and 1(r), respectively) were identified from 74 digitized chest radiographs by two B-readers. Two different texture feature sets were extracted: spatial gray level dependence matrices (SGLDM), and gray level differences statistics (GLDS). The nonparametric Wilcoxon rank sum test was carried out to compare the different profusion categories versus that of profusion 0 (normal). Results showed that significant differences exist (at a=0.05) between 0 versus 1(q), and 0 versus 1(r) for 14, and 12 texture features respectively. For the screening system, the self-organizing map (SOM), the backpropagation (BP), and the radial basis function (RBF) neural network classifiers, as well as the statistical k-nearest neighbour (KNN) classifier were used to classify two classes: profusion 0 and profusion 1(q and r). The highest percentage of correct classifications for the evaluation set (116 and 20 cases of profusion 0 and 1(q and r) respectively) was 75% for the BP classifier for the SGLDM feature set. These results compare favorably with inter- and intra-reader variability. © 2002 IEEE. 2002-January 130 133 Sponsors: IEEE Computer Society Conference code: 115840 Cited By :5
- Subjects :
- Regions of interest
Wilcoxon rank sum test
Wilcoxon signed-rank test
Radiography
Feature extraction
Backpropagation
Diseases
Miners
Mine dust
Conformal mapping
Image analysis
Image texture analysis
Image texture
K nearest neighbours (k-NN)
Diagnosis
medicine
Silicon compounds
Network protocols
Texture feature
Self organizing maps
Image segmentation
Gray level differences
Classifiers
business.industry
Radial basis function neural networks
Pneumoconiosis
Nonparametric statistics
Shape
Pattern recognition
Coal dust
Radial basis function networks
medicine.disease
Computer science
Silica dust
Nearest neighbor search
Artificial intelligence
Lungs
business
Neural networks
Protocols
Coal mines
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- SSIAI, Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 5th IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2002
- Accession number :
- edsair.doi.dedup.....8c74091dfc347108e6fe851927dedbb3