利用深度学习检测帕金森病

K. Sireesha, M. Lahari, N. A. Prasad, N. K. Teja, R. S. Shivani
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引用次数: 0

摘要

帕金森病(PD)是一种长期的神经系统疾病。多巴胺是一种单胺类神经递质。它在大脑的神经细胞之间传递信息。帕金森氏症患者的多巴胺水平较低,因此细胞之间的信息交流很困难。帕金森氏症患者的震颤症状之一就是手抖。我们考虑健康人和帕金森患者绘制的螺旋和波浪图像数据集。所以帕金森氏症患者要画出这些图将是一项艰巨的任务。由于这是一个图像数据集,我们使用两个模型,一个是卷积神经网络,另一个是Densenet 201。这些模型将检验螺旋图和波浪图的画风。因此,我们的项目动机是检测一个人是否患有帕金森病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parkinson’s Disease Detection Using Deep Learning
Parkinson Disease(PD) is a long term neurological disorder. Dopamine is a monoamine neurotransmitter. It performs communication messages between nervous cells in the brain. Person with Parkinson's has low levels of Dopamine so the communication message between cells is tough. Person with Parkinson disease has one symptom of tremor which is hand shaking. We consider the dataset Spiral and Wave images drawn by healthy and Parkinson's people. So, the subject with Parkinson's disorder will have a tough task to draw these diagrams. As this is an image Dataset we are Using two models one is Convolutional Neural Network and Other is Densenet 201. These models will examine the drawing style of spiral and wave drawings. Hence our Project motive is to detect whether a Person has Parkinson Disease or not.
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