Deep Learning for Image Understanding at SPIE Medical Imaging 2018


© Ken Hanson
Fraunhofer MEVIS researcher Markus Wenzel and Hans Meine instructing a 1-day course „Deep Learning for Image Understanding“ at the conference SPIE Medical Imaging 2018 in Houston, Texas.

Deep Learning for Image Understanding at SPIE Medical Imaging 2018

Fraunhofer MEVIS researchers Markus Wenzel and Hans Meine instructed a 1-day course on “Deep Learning for Image Understanding” on Saturday, February 10 as part of this year's SPIE Medical Imaging Conference held February 10–15 in Houston/Texas.

The well-attended and fully booked course was intended for students, researchers, and engineers from academia and industry, who seek to obtain practical working knowledge in deep learning. It enabled almost 70 actively involved participants to:

  • identify the commonly used Deep Learning frameworks (Theano, TensorFlow, CNTK, Caffe, Torch, Lasagne, Keras) and their respective strengths
  • describe the state of the art of deep learning methods in medical applications
  • construct computing pipeline using Python based infrastructure, using the above frameworks
  • select suitable deep learning network architecture for a given problem and implement it
  • explain and interpret learning progress using appropriate metrics
  • interpret the model performance using visual analytics