We propose a nonparametric, probabilistic model for the automatic segmentation of medical images, given a training set of images and corresponding label maps. The resulting inferen...
Mert R. Sabuncu, B. T. Thomas Yeo, Koenraad Van Le...
The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...
Tools for automatic image understanding for managing operator workloads are essential. One common task for image analysts is the scanning large collections of real-time images loo...
We previously presented a HAMMER image registration algorithm that demonstrated high accuracy in superposition of images from different individual brains. However, the HAMMER regis...
Many medical applications require a registration of different images of the same organ. In many cases, such a registration is accomplished by manually placing landmarks in the ima...