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SYSTEMS AND METHODS FOR GENERATING CANCER PREDICTION MAPS FROM MULTIPARAMETRIC MAGNETIC RESONANCE IMAGES USING DEEP LEARNING
SYSTEMS AND METHODS FOR GENERATING CANCER PREDICTION MAPS FROM MULTIPARAMETRIC MAGNETIC RESONANCE IMAGES USING DEEP LEARNING
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机译:使用深度学习从多参数磁共振图像生成癌症预测图的系统和方法
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摘要
Various example embodiments are described in which an anisotropic encoder-decoder convolutional neural network architecture is employed to process multiparametric magnetic resonance images for the generation of cancer predication maps. In some example embodiments, a simplified anisotropic encoder-decoder convolutional neural network architecture may include an encoder portion that is deeper than a decoder portion. In some example embodiments, simplified network architectures may be combined with test-time-augmentation in order to facilitate training and testing with a minimal number of test subjects.
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