AI systems in clinical practice

Medical Imaging Systems
PERFEX
Expert system for automated interpretation of Cardiac SPECT data

developed by clinical domains keywords
Georgia Tech., Emory University Hospital Cardiology, coronary artery disease, 3D Myocardial Perfusion, cardiac SPECT data, diagnosis Expert systems, rules-based systems
location commissioned status
Emory University Hospital 1991 (apprx)  
description
PERFEX is a rule based expert system for automatic interpretation of Cardiac SPECT data. This system infers the extent and severity of coronary artery disease (CAD) from perfusion distributions, and provides as output a patient report summarizing the condition of the three main arteries and other pertinent information. The overall goal is to assist in the diagnosis of coronary artery disease. The approach employs knowledge based methods to process and map the 3D visual information into symbolic representations, which are subsequently used to infer structure (anatomy) from function (physiology), as well as to interpret the temporal effects of perfusion redistribution, and assess the extent and severity of cardiovascular disease both quantitatively and qualitatively. The knowledge based system presents the resulting diagnostic recommendations in both visual and textual forms in an interactive framework, thereby enhancing overall utility.

At present, PERFEX is implemented in an object oriented environment using Neuron Data's Nexpert Object. This object oriented framework provides a some advantages, including inheritance properties and C code. This software, however, has been extensively modified to incorporate the CF Model (which is intimately linked to inferencing) and to allow for a dynamic user interface. The system underwent extensive evaluation - including multi- centre testing, followed by filing for FDA approval. The system itself has been already ported to a commercial clinical system.

references

N. F.Ezquerra and R. Mullick and E. V. Garcia and C. D. Cooke and E. Kachouska, PERFEX: An Expert System for Interpreting 3D Myocardial Perfusion", Expert Systems with Applications, Pergamon Press, (1992)

[]   []

" "

R. Mullick and N. F. Ezquerra and E. V. Garcia and C. D. Cooke, A Knowledge- Based System to Assist in the Diagnosis of Coronary Artery Disease, Proceedings of the Tenth Southern Biomedical Engineering Conference, 107-9, 1991

[]   []

" "

R. Mullick and N. F. Ezquerra, Research in Medical Informatics at Georgia Tech.: An Overview, Proceedings of the 1991 IEEE Region 10 International Conference on Energy, Computer, Communications, and Control Systems - TENCON `91 New Delhi, INDIA, 2, 63-70, 1991

[]   []

" "

N. F. Ezquerra and E. V. Garcia, Artificial Intelligence in Nuclear Medicine Imaging, American Journal of Cardiac Imaging, 3, 2, 130-41, 1989

[]   []

" "

E. V. Garcia and M. D. Herbst and C. D. Cooke and N. F. Ezquerra and B. L. Evans and R. D. Folks and E. G. DePuey, Knowledge-based Visualization of myocardial perfusion tomographic images, vbc90, 157-61, 1990

[]   []

" "

contact links
Georgia Tech., Emory University Hospital.

 bullet  PERFEX
acknowledgements

Archive of AI systems in clinical practice previously administered by Enrico Coiera. Used with permission. Maintained and extended since 2001 by OpenClinical.

Entry on archive: March 23 1993
Last main update: March 13 1996
Search this site
 

 

Privacy policy User agreement Copyright Feedback

Last modified:
© Copyright OpenClinical 2002-2011