A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
We develop a Bayesian model of digitized archival films and use this for denoising, or more specifically de-graining, individual frames. In contrast to previous approaches our mod...
Teodor Mihai Moldovan, Stefan Roth, Michael J. Bla...
We study the problem of visualizing large networks and develop es for effectively abstracting a network and reducing the size to a level that can be clearly viewed. Our size reduc...
Recent advances in biophotonics have enabled in-vivo, in-situ histopathology for routine clinical applications. The non-invasive nature of these optical `biopsy' techniques, h...
Selen Atasoy, Ben Glocker, Stamatia Giannarou, ...
General graph matching methods often suffer from the lack of mathematical structure in the space of graphs. Using kernel functions to evaluate structural graph similarity allows u...