Adaptive multiple feature method (AMFM) for early detecton of parenchymal pathology in a smoking population

Renuka Uppaluri; Geoffrey McLennan; Paul Enright; James Standen; Pamela Boyer-Pfersdorf; Eric A Hoffman

doi:10.1117/12.312563

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Adaptive multiple feature method (AMFM) for early detecton of parenchymal pathology in a smoking population

Conference proceeding

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Adaptive multiple feature method (AMFM) for early detecton of parenchymal pathology in a smoking population

Renuka Uppaluri, Geoffrey McLennan, Paul Enright, James Standen, Pamela Boyer-Pfersdorf and Eric A Hoffman

Proceedings of SPIE, Vol.3337(1), pp.8-13

Medical Imaging 1998: Physiology and Function from Multidimensional Images

07/03/1998

DOI: 10.1117/12.312563

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Abstract

Application of the Adaptive Multiple Feature Method (AMFM) to identify early changes in a smoking population is discussed. This method was specifically applied to determine if differences in CT images of smokers (with normal lung function) and non-smokers (with normal lung function) could be found through computerized texture analysis. Results demonstrated that these groups could be differentiated with over 80.0% accuracy. Further, differences on CT images between normal appearing lung from non-smokers (with normal lung function) and normal appearing lung from smokers (with abnormal lung function) were also investigated. These groups were differentiated with over 89.5% accuracy. In analyzing the whole lung region by region, the AMFM characterized 38.6% of a smoker lung (with normal lung function) as mild emphysema. We can conclude that the AMFM detects parenchymal patterns in the lungs of smokers which are different from normal patterns occurring in healthy non-smokers. These patterns could perhaps indicate early smoking-related changes.

Details

Title: Subtitle: Adaptive multiple feature method (AMFM) for early detecton of parenchymal pathology in a smoking population
Creators: Renuka Uppaluri - University of Iowa
Geoffrey McLennan - University of Iowa
Paul Enright - University of Arizona
James Standen - University of Arizona
Pamela Boyer-Pfersdorf - University of Arizona
Eric A Hoffman - University of Iowa
Resource Type: Conference proceeding
Publication Details: Proceedings of SPIE, Vol.3337(1), pp.8-13
Conference: Medical Imaging 1998: Physiology and Function from Multidimensional Images
DOI: 10.1117/12.312563
ISSN: 0277-786X
Language: English
Date published: 07/03/1998
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Internal Medicine
Record Identifier: 9984318688902771

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