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Localization of Demyelinating Plaques in MRI using Convolutional Neural Networks

机译:利用卷积神经网络将MRI脱髓鞘的本地化

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In the paper a method of demyelinating plaques localization in head MRI sequences is presented. For that purpose a convolutional neural network is used. It is trained to act as non-linear filter, which should indicate (give a high response) in those image areas where the sought objects are located. Consequently, the output of the proposed architecture is an image and not a single label as it is in the case of traditional networks with pooling and fully connected layers. Another interesting feature of the proposed solution is the ability to select network parameters using smaller patches cut from training images which reduces the amount of data that must be propagated through the network. It should be emphasized that the conducted research was possible only thanks to the manually outlined plaques provided by radiologist.
机译:在本文中,提出了一种脱髓鞘凝结斑块定位的方法。为此目的使用卷积神经网络。它训练以充当非线性滤波器,其应该在所寻求的物体所在的那些图像区域中指示(在那些高响应)中。因此,所提出的架构的输出是图像而不是单个标签,因为它在具有池和完全连接的层的传统网络的情况下。所提出的解决方案的另一个有趣特征是使用从训练图像中切割的较小贴片来选择网络参数,这减少了必须通过网络传播的数据量。应该强调的是,只有放射科医师提供的手动概述的斑块,就可以进行进行的研究。

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