Nicholas Ayache
INRIA, France

Lecture 1
“Part 1: The role of anatomical and physiological models in Medical Imaging Computing”

Lecture 2
“Part 2:Biophysical simulation of medical images with pathologies for Machine Learning”

Marleen de Bruijne
University of Copenhagen, Denmark and Erasmus MC - University Medical Center Rotterdam, The Netherlands

Lecture 1
“Learning imaging biomarkers: challenges and pitfalls”

Lecture 2
“Learning from weak labels”

Ben Glocker
Imperial College London, United Kingdom

Lecture 1
“Random Forests and their applications in medical imaging”

Lecture 2
“Solving continuous problems with discrete optimization: Tracking and Registration with Markov Random Fields”

Lecture 3
“Deep Learning for Brain Lesion Segmentation”

Alison Noble
University of Oxford, United Kingdom

Lecture 1
“Popular Classics in Machine Learning for Medical Imaging”

Lecture 2
“Learning to interpret Ultrasound Imaging”

Carsten Rother
Technische Universität Dresden, Germany

Lecture 1
“Introduction to Graphical Models”

Lecture 2
“Graphical Models in BioImaging”

Daniel Rueckert
Imperial College London, United Kingdom

Lecture 1
“Manifold learning, dictionary learning & sparsity”

Lecture 2
“Machine learning for segmentation and reconstruction”

Raquel Urtasun
University of Toronto, Canada

Lecture 1
“Introduction to Convolutional Neural Networks”

Lecture 2
“Learning Deep Structured Models”

Andrea Vedaldi
University of Oxford, United Kingdom

Lecture 1
“Advanced Convolutional Neural Networks”

Lecture 2
“Understanding CNNs using visualisation and transformation analysis”

Max Welling
University of Amsterdam, The Netherlands

Lecture 1
“Approximate Bayesian Posterior Inference for Big Data”

Lecture 2
“A Unifying Framework for Deep Learning, Graphical Models and Bayesian Estimation”

William M. Wells III (aka Sandy Wells)
Harvard Medical School and MIT CSAIL, USA

Lecture 1
“A Graphical Introduction to Probabilistic Graphical Models”

Lecture 2
“Real Slow Registration: Exploratory Work on Uncertainty in Registration with MCMC”

Lecture 3
“Excellent Magic: A multi-perspective introduction to the EM algorithm”

RULES OF ENGAGEMENT

POSTERS SUBMITTED TO MISS 2016