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Automated staging of coal workers' pneumoconiosis utilizing digital image analysis of chest x-rays.

Authors
Preston-K Jr.; Witt-EK
Source
Electrical and Computer Engineering Department and Biomedical Engineering Program, Carnegie Mellon University, Pittsburgh, Pennsylvania 1996 Feb; :1-15
Link
NIOSHTIC No.
00235019
Abstract
This final report covers research designed to determine the feasibility of automated staging of coal workers' pneumoconiosis (CWP) using digital image analysis of chest X-rays. A system which can potentially aid the radiologist in the classification of CWP from chest X-rays is described. The system applies statistical pattern recognition to digitized CWP chest X-ray images based on the generation of features from the matrix of numbers that represents the digitized films, and the application of a variety of algorithms that may be used to distinguish profusion and opacity size. Both traditional (2-D Fourier transform and the spatial gray level dependence matrix) and new (minimum tracking algorithm and the Gauss- Markov random field parameters) feature sets were used; 386 features were included. Comparison of an expert radiologist's classifications with those of other radiologists yielded correlation coefficients of 0.60 and 0.82 for profusion and opacity size, respectively. When the expert's classifications were compared to the computer classifications, the correlation coefficients were 0.56 for profusion and 0.55 for opacity size. The authors conclude that ultimately the classifier and visualization tools described can be used in a preliminary chest X-ray screening system which would identify regions possibly exhibiting pathology, and indicate these regions to the radiologist.
Keywords
NIOSH-Grant; Pulmonary-system-disorders; Diagnostic-techniques; Coal-workers-pneumoconiosis; Respiratory-system-disorders; Lung-disease; Occupational-respiratory-disease
Contact
Electrical Engineering Carnegie Mellon University 5000 Forbes Ave Pittsburgh, PA 15213
Publication Date
19960226
Document Type
Final Grant Report
Funding Amount
65474
Funding Type
Grant
Fiscal Year
1996
NTIS Accession No.
PB97-147268
NTIS Price
A03
Identifying No.
Grant-Number-R01-OH-03055
NIOSH Division
OEP
Priority Area
Respiratory-system-disorders
Source Name
Electrical and Computer Engineering Department and Biomedical Engineering Program, Carnegie Mellon University, Pittsburgh, Pennsylvania
State
PA
Performing Organization
Carnegie-Mellon University, Pittsburgh, Pennsylvania
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