Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing th...
Mert R. Sabuncu, B. T. Thomas Yeo, Koen Van Leem...
Abstract. The goal of this paper is to present a novel recipe for deformable image registration under varying illumination, as a natural extension of the demons algorithm. This gen...
Challenging object detection and segmentation tasks can be facilitated by the availability of a reference object. However, accounting for possible transformations between the diff...
Research presented in this paper deals with the systematic examination, development, and evaluation of a novel multimodal registration approach that can perform accurately and rob...
In this paper, we present a novel framework for constructing large deformation log-unbiased image registration models that generate theoretically and intuitively correct deformati...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...