WeAidU-a decision support system for myocardial perfusion images using artificial neural networks.
This paper presents a computer-based decision support system for automated interpretation of diagnostic heart images (called WeAidU), which is made available via the Internet. The system is based on image processing techniques, artificial neural networks (ANNs) and large well-validated medical databases. We present results using artificial neural networks, and compare with two other classification methods, on a retrospective data set containing 1320 images from the clinical routine. The performance of the artificial neural networks detecting infarction and ischemia in different parts of the heart, measured as areas under the receiver operating characteristic curves, is in the range 0.83-0.96. These results indicate a high potential for the tool as a clinical decision support system.
Ohlsson
Mattias
M
Department of Theoretical Physics, Lund University, Sölvegatan 14A, SE-223 62, Lund, Sweden. mattias@thep.lu.se
D001331:Automation; D017023:Coronary Angiography; D003658:Decision Making, Computer-Assisted; D006801:Humans; D020407:Internet; D009203:Myocardial Infarction / Q000175:diagnosis* / Q000628:therapy; D017202:Myocardial Ischemia / Q000000981:diagnostic imaging*; D015425:Myocardial Reperfusion; D016571:Neural Networks, Computer; D011877:Radionuclide Imaging; D012189:Retrospective Studies