Answers.Body: <p>It looks like everything you want is available with the <a href="https://dltk.github.io/" rel="nofollow noreferrer">Deep Learning Toolkit (DLTK) for Medical Imaging</a></p>
  
  <p>There is also a blog: <a href="https://blog.tensorflow.org/2018/07/an-introduction-to-biomedical-image-analysis-tensorflow-dltk.html" rel="nofollow noreferrer">An Introduction to Biomedical Image Analysis with TensorFlow and DLTK</a></p>
  
  <p>There is a DataCamp course that walks you through most of the process but instead of a classifier they use deep learning to reconstruct brain images.  They provide a link to their MNIST classifier example which should be easy to adapt for your purpose.  See: <a href="https://www.datacamp.com/community/tutorials/reconstructing-brain-images-deep-learning" rel="nofollow noreferrer">Reconstructing Brain MRI Images Using Deep Learning (Convolutional Autoencoder)</a></p>
  
  <p>ResearchGate has a thread that may help:
  <a href="https://www.researchgate.net/post/What_is_the_appropriate_way_to_use_Nifti_files_in_deep_learning" rel="nofollow noreferrer">What is the appropriate way to use Nifti files in deep learning?</a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-05-14T11:44:54.723Z
Answers.LastActivityDate: 2020-05-14T12:18:19.260Z
Answers.LastEditDate: 2020-05-14T12:18:19.260Z
Answers.UserDisplayName: Brian O'Donnell
Body: <p>I have a dataset with <strong>MRI</strong> of patients with a specific disease that affects the <strong>brain</strong> and another dataset with <strong>MRI</strong> of healthy patients.</p>
  
  <p>I want to create a <strong>classifier</strong> (using neural networks) to classify if the MRI of a new patient shows the presence of the illness or not.</p>
  
  <p>First of all, I <strong>extracted</strong> the brain from all the MRIs (the so-called <strong>skull stripping</strong>) using <a href="https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/BET" rel="nofollow noreferrer">BET</a> tool found in FSL.</p>
  
  <p>I have three questions for you</p>
  
  <ol>
  <li><p>As the input to the <strong>training</strong> phase, I want to give the <strong>whole</strong> extracted brains (possibly in the nii format). What kind of <strong>preprocessing</strong> steps do I need to apply once I've <strong>extracted</strong> the brains (before passing it to the classifier)?</p></li>
  <li><p>Do you know any better tool for <strong>skull stripping</strong>?</p></li>
  <li><p>Do you know a tool (or library) that takes as input a nii files and allows me to create a classifier that uses neural networks?</p></li>
  </ol>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-05-14T10:29:23.357Z
Comments.Text: Please, focus on one question only. I would remove at least the second question and maybe leave the 3rd question as a side note.
Comments.UserDisplayName: nbro
Tags: <neural-networks><machine-learning><data-preprocessing><brain>
Title: Are my steps correct for a proper classification of a sick brain?
UserDisplayName: AleWolf
ThreadText: # Are my steps correct for a proper classification of a sick brain?
  
  (Asked by: username_0 on 2020-05-14)
  
  I have a dataset with **MRI** of patients with a specific disease that affects the **brain** and another dataset with **MRI** of healthy patients.
  
  I want to create a **classifier** (using neural networks) to classify if the MRI of a new patient shows the presence of the illness or not.
  
  First of all, I **extracted** the brain from all the MRIs (the so-called **skull stripping**) using [BET](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/BET) tool found in FSL.
  
  I have three questions for you
  
  1. As the input to the **training** phase, I want to give the **whole** extracted brains (possibly in the nii format). What kind of **preprocessing** steps do I need to apply once I've **extracted** the brains (before passing it to the classifier)?
  2. Do you know any better tool for **skull stripping**?
  3. Do you know a tool (or library) that takes as input a nii files and allows me to create a classifier that uses neural networks?
  
  **Tags:** neural-networks, machine-learning, data-preprocessing, brain
  
  > **Comments:**
  > **username_1**: Please, focus on one question only. I would remove at least the second question and maybe leave the 3rd question as a side note.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2020-05-14. Score: 2
  
  It looks like everything you want is available with the [Deep Learning Toolkit (DLTK) for Medical Imaging](https://dltk.github.io/)
  
  There is also a blog: [An Introduction to Biomedical Image Analysis with TensorFlow and DLTK](https://blog.tensorflow.org/2018/07/an-introduction-to-biomedical-image-analysis-tensorflow-dltk.html)
  
  There is a DataCamp course that walks you through most of the process but instead of a classifier they use deep learning to reconstruct brain images. They provide a link to their MNIST classifier example which should be easy to adapt for your purpose. See: [Reconstructing Brain MRI Images Using Deep Learning (Convolutional Autoencoder)](https://www.datacamp.com/community/tutorials/reconstructing-brain-images-deep-learning)
  
  ResearchGate has a thread that may help:
  [What is the appropriate way to use Nifti files in deep learning?](https://www.researchgate.net/post/What_is_the_appropriate_way_to_use_Nifti_files_in_deep_learning)
  
  
  ---
  
  