=============================
Experiments on ADNI Database
=============================

Click here_ for more information about the database.

.. _here: http://adni.loni.usc.edu/

Preparation
^^^^^^^^^^^^

Get the raw data
################
Get raw data from here_.

Serialize the raw data
######################

Use the following command to run the serialization:

.. code-block:: console

   python -m datasets.brain.serialize -m sacred


Unconditioned brain GAN
^^^^^^^^^^^^^^^^^^^^^^^

The following experiment shows how to generate random brains with
the GanEstimator_ module. For implementation details see :ref:`components_label` or :ref:`API_label`

To run the code with the default parameters defined in the config function
just type from the root directory:

.. code-block:: console

   python -m exps.brain.train

Or use the command line arguments to set different parameters:

.. code-block:: console

   python -m exps.brain.train with brain_feeder.batch_size=16

.. _GanEstimator: https://www.tensorflow.org/api_docs/python/tf/contrib/gan/estimator/GANEstimator

Example output
###############
With the default parameters we will obtain the following result for training steps 100, 1000 and 2000:

.. raw:: html

   <iframe src="../_static/slider_brain.html" height="600px" width="600px" frameborder=0></iframe>