神经网络和卷积算法在电子医学中的应用

T. Rymarczyk, Barbara Stefaniak, P. Adamkiewicz
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引用次数: 1

摘要

该解决方案展示了数据采集和分析系统的体系结构。有人试图开发图像分割算法。需要这些算法来识别分割问题的任意数量的相位。通过使用水平集方法、神经网络和深度学习方法等算法,它可以获得更快的诊断,并自动标记医学图像中的感兴趣区域。
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NEURAL NETWORK AND CONVOLUTIONAL ALGORITH TO EXTRACT SHAPES BY E-MEDICUS APPLICATION
The solution shows the architecture of the system collecting and analyzing data. There was tried to develop algorithms to image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. With the use of algorithms such as the level set method, neural networks and deep learning methods, it can obtain a quicker diagnosis and automatically marking areas of the interest region in medical images.
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
40
审稿时长
10 weeks
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