Workshop / Overview

A generative adversarial network (GAN) is a pair of deep neural networks: a generator that creates new examples based on the training data provided and a discriminator that attempts to distinguish between genuine and simulated data. As both networks improve together, the examples created become increasingly realistic. This technology is promising for healthcare, because it can augment smaller datasets for training of traditional networks. At this hands-on workshop you'll learn to:

  • Generate synthetic brain MRIs
  • Apply GANs for segmentation
  • Use GANs for data augmentation to improve accuracy

Workshop / Outcome

Upon completion, you'll be able to apply GANs to medical imaging use cases.

Workshop / Difficulty

Intermediate level

Workshop / Prerequisites

Experience with CNNs

Follow these steps prior to joining the training:

  • You must bring your own laptop in order to run the training.
  • A current browser is needed. For optimal performance, Chrome, Firefox or Safari for Macs are recommended. IE is operational but does not provide the best performance.
  • Create an account at
  • Ensure your laptop will run smoothly by going to
  • Make sure that WebSockets work for you by seeing under Environment, WebSockets is supported and Data Receive, Send and Echo Test all check Yes under WebSockets (Port 80).
  • If there are issues with WebSockets, try updating your browser.

Track / Co-organizers

Nicola Rieke

Senior Deep Learning Solution Architect – Healthcare, NVIDIA

Cristiana Dinea

Master Instructor, NVIDIA Deep Learning Institute

AMLD EPFL 2019 / Workshops

TensorFlow Basics 2019 – Saturday

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09:00-16:30 January 26

Document Digitization Challenge

With Mihai Gurban & Raquel Terrés Cristofani

09:00-16:30 January 262A

TensorFlow Basics 2019 – Sunday

With Bartek Wołowiec, Megan Ruthven, Ruslan Habalov & Andreas Steiner

09:00-16:30 January 274ABC

AMLD / Global partners