n South African Computer Journal - Investigating the use of multiresolution image processing and artificial neural networks for computer-aided diagnosis within a telemedicine network
|Article Title||Investigating the use of multiresolution image processing and artificial neural networks for computer-aided diagnosis within a telemedicine network|
|© Publisher:||South African Computer Society (SAICSIT)|
|Journal||South African Computer Journal|
|Author||B. Aydn Alaylolu and F Aghdasi|
|Publication Date||Nov 2000|
|Pages||115 - 124|
|Keyword(s)||Artificial neural networks, Computer-aided diagnosis (CAD), DICOM, G.1.2, I.4.3, I.4.6, I.4.7, I.4.9, I.5.4, Image processing, J.3, Machine intelligence, Pattern recognition and Telemedicine|
In image processing and pattern recognition, the usefulness of extracted image features and classifiers are assessed according to their accuracy in classifying new data, such as assigning a diagnostic decision to digitised medical images. In such applications, predictive classifiers are a valuable tool only if they increase the number of true detections while minimising the occurrence of false predictions. A computer-automated detection scheme, making use of an artificial neural network classifier, with input feature vectors containing spatial, spectral and multiscale image attributes, is investigated here with an objective to improve the efficiency of the medical diagnostic processes. A wavelet-based image enhancement technique is also implemented, with the aim of improving the computer-automated detection performance. the incorporation of the CAD workstations into a telemedicine service network and biomedical informatics systems to meet the challenges of the new millennium is described.
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