Application Of Dynamic Segmentation In Stroke Detection Software With ANN

Abstract

One way to find out whether there is a stroke is to do a CT scan . But the results of the examination with a new CT scan can be obtained in quite a long time. In addition, sometimes there are differences of opinion between doctors and radiologists regarding what is seen from the results of the examination. This research was conducted to produce a software that can later be integrated with the existing system on the CT Scan tool so that it can immediately be known whether or not stroke is present from the CT Scan results. In this study, a dynamic image segmentation method is implemented, namely the watershed transformation method which will later produce regions as a feature for the stroke detection process carried out with the backpropagation algorithm. From experiments conducted on CT scan images of the brain, this method can detect stroke well. The results obtained are 100% for training data and 90% for test data.

Neural Network-Based Dynamic Segmentation and Weighted Integrated Matching of Cross-Media Piano Performance Audio Recognition and Retrieval Algorithm

“…In past research, many approaches used the above ideas to solve cross-media retrieval problems. ey can be broadly classified into three categories: subspace-based methods, hash-based methods, and deep learning-based methods [8]. Subspace approaches can learn mapping matrices using pairs of multimedia data information to project different types of media data into a common subspace.…”