Loic Le Folgoc, Microsoft Research, Cambridge UK
26 July 2017, 1:00 pm–2:00 pm
Event Information
Open to
- All
Location
-
UCL Bloomsbury - Roberts 106 Roberts building
Title:
Learning structure in complex data: Bayesian models, discriminative models and the models in between for medical image analysis.
Abstract:
The amount of raw medical scans available to us increases rapidly, but expert manual annotations often remain scarce and costly. I will present approaches that leverage the latent spatial structure and rich image semantics to generalize better from small annotated datasets, despite variability introduced by subject anatomies, acquisition protocol & imaging quality. We will cover applications to motion tracking and segmentation tasks. I will unabashedly range from Bayesian modelling techniques to auto-context forest architectures, before exploring forest-based message-passing models that seamlessly integrate fully automatic & user-assisted capabilities.