DocumentCode :
3622236
Title :
Interpretation of Uroflow Graphs with Artificial Neural Networks
Author :
Altunay; Telatar; Erogul; Aydur
Author_Institution :
EAS Elektronik Sanayi Ticaret A.Ş
fYear :
2006
fDate :
6/28/1905 12:00:00 AM
Firstpage :
1
Lastpage :
4
Abstract :
Uroflowmetry is a measuring method, which provides numerical and graphical information about patient´s lower urinary tract dynamics by measuring and plotting the rate of change of voided urine volume. The main purpose of the study is to evaluate uroflowmetric data using artificial neural networks (ANN) and provide a pre-diagnostic result for urology specialists. The ANN is trained using back-propagation method and the inputs of ANN are the results of a special feature extraction algorithm, which is designed with the suggestions of urology specialists. System´s success is monitored with a set of data, which was already diagnosed by specialists. The outputs of ANN are classified into three groups, namely, "healthy", "possible pathologic" and "pathologic"
Keywords :
"Artificial neural networks","Volume measurement","Testing","Argon","Feature extraction","Algorithm design and analysis","Monitoring","Abdomen","Medical diagnostic imaging"
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications, 2006 IEEE 14th
ISSN :
2165-0608
Print_ISBN :
1-4244-0238-7
Type :
conf
DOI :
10.1109/SIU.2006.1659698
Filename :
1659698
Link To Document :
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