Noninvasive examination analysis system for cardiovascular surgeon / phlebologist decision-making support

This study discusses a system for analyzing noninvasive examination results to support the decision-making by a cardiovascular surgeon/phlebologist. The software helps the phlebologist in making decisions to determine the CEAP classification code in controversial and complicated cases. The system recognizes uploaded DICOM format images with a convolutional neural network.
Contrast enhancement of b/w DICOM images was applied for the neural network training. It improves the image handling and increases the recognition accuracy. The average recognition rate is from 86.1 to 97.4 %.