Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network

  title={Alzheimer's Disease Diagnostics by a Deeply Supervised Adaptable 3D Convolutional Network},
  author={Ehsan Hosseini-Asl and G. Gimel'farb and A. El-Baz},
  • Ehsan Hosseini-Asl, G. Gimel'farb, A. El-Baz
  • Published 2016
  • Computer Science, Biology, Mathematics
  • ArXiv
  • Early diagnosis, playing an important role in preventing progress and treating the Alzheimer's disease (AD), is based on classification of features extracted from brain images. The features have to accurately capture main AD-related variations of anatomical brain structures, such as, e.g., ventricles size, hippocampus shape, cortical thickness, and brain volume. This paper proposes to predict the AD with a deep 3D convolutional neural network (3D-CNN), which can learn generic features capturing… CONTINUE READING
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