Probabilistic Morphable Models are a fully probabilistic approach to model-based image analysis, based on:
This course teaches the theoretical basis of shape modelling and model fitting and provides an introduction on how to use the software framework Scalismo. The participants will apply the learned concepts and methods in a course project, whose goal it is to develop an interactive, model-based segmentation application.
The course consists of two parts: An open online course and a summer school.
In the online course, participants learn the basic theory of shape modelling and are given a practical introduction to Scalismo. Participants of this course, who submit a solution to the course project, are invited to attend the summer school.
The summer school will focus on model-based image analysis. In theory lectures, participants will learn more about model-fitting and registration, with particular emphasis on probabilistic model-fitting using Markov Chain Monte Carlo methods. An important part of the summer-school is the course project. The participants will implement a complete application for interactive model-based segmentation of medical images using the open source framework Scalismo.
The intended audience for the course is beginning graduate students and researchers from academia and industry interested in shape and image analysis.
Prerequisite is knowledge of basic probability theory and statistics as well as linear algebra. Participants should have good programming skills in at least one programming language (ideally Java, C++ or Python).
|Mon 2/17||Sun 2/23||Basic concepts of shape modelling and the scalismo software.|
|Mon 2/24||Sun 3/1||Building shape models: fundamental concepts in theory and practice.|
|Mon 3/2||Sun 3/8||Probabilistic aspects of shape models.|
|Mon 3/9||Sun 3/15||Modelling with Gaussian Processes|
|Mon 3/16||Sun 3/22||Reconstructing missing parts|
|Mon 3/23||Sun 3/29||Fitting models to data|
|Mon 3/30||Sun 4/5||Model-based image analysis|
|Mon 4/6||Sun 4/12||Course Project|
|Mon 6/29||Analysis-by-synthesis and non-rigid registration|
|Tue 6/30||Bayesian inference and probabilistic model fitting|
|Wed 7/1||Beyond segmentation: Applications of shape modelling in biomedical image analysis|
|Thu 7/1||Advanced topics in Gaussian processes and MCMC|
|Fri 7/3||The computer vision perspective: Automated analysis of 2D face images|
To registration for the online course, please go directly to FutureLearn.
To register for the summer school, please send an e-mail to the address below. Note that the summer school is free of charge, but requires some investment of time from your side. A prerequisite for admission is the successfully completion the course project, which is part of the online course.