Convolutional Neural Networks For Identification Of Axial 2d Slices In Ct Data

Abstract

This thesis deals with the classification of 2D axial slices in CT patient’s data. The classification is realized into six categories. The sphere of convolutional neural networks was used for this purpose and AlexNet network was specifically selected for the intention of this identification, which was applied to the created data set after being adaptated. The overall classification success rate was 84%. In addition, an analysis of mistakes in classification was performed.