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      CDeep3M - Plug-and-Play cloud based deep learning for image segmentation of light, electron and X-ray microscopy

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          Abstract

          As biological imaging datasets increase in size, deep neural networks are considered vital tools for efficient image segmentation. While a number of different network architectures have been developed for segmenting even the most challenging biological images, community access is still limited by the difficulty of setting up complex computational environments and processing pipelines, and the availability of compute resources. Here, we address these bottlenecks, providing a ready-to-use image segmentation solution for any lab, with a pre-configured, publicly available, cloud-based deep convolutional neural network on Amazon Web Services (AWS). We provide simple instructions for training and applying CDeep3M for segmentation of large and complex 2D and 3D microscopy datasets of diverse biomedical imaging modalities.

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          (View ORCID Profile)
          Journal
          bioRxiv
          June 21 2018
          Article
          10.1101/353425
          99626b1d-9c3c-4ac6-b51a-23e47bd9fe08
          © 2018
          History

          Cell biology,Comparative biology
          Cell biology, Comparative biology

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