Search Results for author: Terry M. Peters

Found 6 papers, 0 papers with code

A Continuous Max-Flow Approach to Cyclic Field Reconstruction

no code implementations11 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.

Image Reconstruction

Shape Complexes in Continuous Max-Flow Hierarchical Multi-Labeling Problems

no code implementations15 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.

Image Segmentation Segmentation +1

A Proximal Bregman Projection Approach to Continuous Max-Flow Problems Using Entropic Distances

no code implementations30 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.

Segmentation

A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization

no code implementations5 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.

Segmentation

RANCOR: Non-Linear Image Registration with Total Variation Regularization

no code implementations9 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.

Brain Segmentation Image Registration

A Continuous Max-Flow Approach to General Hierarchical Multi-Labeling Problems

no code implementations1 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.

Clustering Segmentation

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