no code implementations • 11 Nov 2015 • John S. H. Baxter, Jonathan McLeod, Terry M. Peters
Reconstruction of an image from noisy data using Markov Random Field theory has been explored by both the graph-cuts and continuous max-flow community in the form of the Potts and Ishikawa models.
no code implementations • 15 Oct 2015 • John S. H. Baxter, Jing Yuan, Terry M. Peters
Although topological considerations amongst multiple labels have been previously investigated in the context of continuous max-flow image segmentation, similar investigations have yet to be made about shape considerations in a general and extendable manner.
no code implementations • 30 Jan 2015 • John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters
One issue limiting the adaption of large-scale multi-region segmentation is the sometimes prohibitive memory requirements.
no code implementations • 5 May 2014 • John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters
The incorporation of region regularization into max-flow segmentation has traditionally focused on ordering and part-whole relationships.
no code implementations • 9 Apr 2014 • Martin Rajchl, John S. H. Baxter, Wu Qiu, Ali R. Khan, Aaron Fenster, Terry M. Peters, Jing Yuan
Optimization techniques have been widely used in deformable registration, allowing for the incorporation of similarity metrics with regularization mechanisms.
no code implementations • 1 Apr 2014 • John S. H. Baxter, Martin Rajchl, Jing Yuan, Terry M. Peters
Multi-region segmentation algorithms often have the onus of incorporating complex anatomical knowledge representing spatial or geometric relationships between objects, and general-purpose methods of addressing this knowledge in an optimization-based manner have thus been lacking.