Skip to content

NadiaBlostein/McMedhacks_MRIs-and-GANs

 
 

Repository files navigation

McMedhacks_MRIs-and-GANs

Open In Colab

McMed Hacks 2021 was an 8-week long series of talks and workshops on medical imaging analysis and deep learning in Python. As mentors for week 6, we were in charge of preparing an assignment on the topic of MR and GAN-based segmentation, as well as hosting tutorials and answering participant questions.

cropped-cropped-cropped-ColoredMedHacksLogo-e1622247024146-1

Assignment Part 1:

This portion of the assignment overviews magnetic resonance imaging (MRI), the differences between T1w and T2w image and how to handle MRI images in Python.

Assignment Part 2:

This portion of the assignment is designed to allow participants to gain hands-on experience in implementing a simple generative adversarial network (GAN) using the MNIST handwritten digit dataset. During the week 6 workshop, participants also had the opportunity to take a look at how the algorithm proposed in "Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks" generates MRI data.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%