NDLI: Automated diagnosis of pneumoconiosis (black lung): A feasibility study

Content Provider	IEEE Xplore Digital Library
Author	Kahveci, A.E. Dwyer, S.J. Lodwick, G.S.
Copyright Year	1972
Description	Author affiliation: University of Missouri-Columbia, Columbia, Missouri (Kahveci, A.E.; Dwyer, S.J.; Lodwick, G.S.)
Abstract	The feasibility of automatic diagnosis of pneumoconiosis using digital image analysis techniques was investigated. Normal/abnormal diagnosis was done first. Differential diagnosis was not attempted at this stage. Normal/abnormal classification scheme is based on a technique which makes use of individual lung lobe histograms. The magnitude of the first relative peak in the normalized histogram indicates the extent of the nodular patterns that characterize pneumoconiosis. For the abnormal lung lobe this value is higher than that for a normal one. This criterion is used for normal/abnormal classification. The results are encouraging enough to propose an automated pneumoconiosis diagnosis system. Differential diagnosis will be attempted by analyzing the nodular lung pattern. The size, number, and location of the nodularities will be used for differential diagnosis.
Starting Page	605
Ending Page	608
File Size	872352
Page Count	4
File Format	PDF
DOI	10.1109/CDC.1972.269083
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1972-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lungs Diseases Image analysis Histograms Laboratories Radiology Diagnostic radiography
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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