Application Of Dynamic Segmentation In Stroke Detection Software With ANN

Hastie Audytra, Julian Supardi, Abdiansah Abdiansah
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引用次数: 2

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.
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动态分割在脑卒中检测软件中的应用
确定是否有中风的一种方法是做CT扫描。但是用新的CT扫描检查的结果需要相当长的时间才能得到。此外,有时医生和放射科医生对检查结果的看法也存在分歧。这项研究是为了开发一种软件,该软件可以与CT扫描工具上的现有系统集成,这样就可以立即从CT扫描结果中得知是否存在中风。在本研究中,实现了一种动态图像分割方法,即分水岭变换方法,该方法将生成区域作为特征,用于反向传播算法进行的笔画检测过程。通过对脑CT扫描图像的实验,该方法可以很好地检测脑卒中。训练数据的结果为100%,测试数据的结果为90%。
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