CamNet Layer 2

A deep learning platform for digital histopathology. This 2nd layer used the patches extracted by layer I to train a convolutional neural network.

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18 commits | Last update: October 28, 2020

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What CamNet Layer 2 can do for you

  • Provides a state-of-the art neural network
  • Based on proven technology such as Keras and Tensorflow
  • Supports GPU acceleration

CamNET is a deep learning platform for digital histopathology aimed at detecting tumor tissue in gigapixel scans of slides containing breast lymph nodes tissue. Currently, a 'human' expert needs to inspect these slides in order to find suspected tumors, which is very labor intensive. CamNET attempts to automate this using a deep learning approach.

This 2nd layer used the patches and labels extracted by layer I to train a convolutional neural network to classify the two patch types. Different models can be chosen by a configuration parameter. Keras and Tensorflow are used to implement this layer.

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Tags
  • Medical image data
  • Image processing
  • Machine learning
Programming Language
  • Python
License
  • MIT
Source code

Participating organizations

Contributors

  • Mara Graziani
    Haute École Spécialisée de Suisse Occidentale HES-SO Valais (HESSO)
Contact person
Mara Graziani
Haute École Spécialisée de Suisse Occidentale HES-SO Valais (HESSO)

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