This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
A novel method for the segmentation of multiple objects from 3D medical images using inter-object constraints is presented. Our method is motivated by the observation that neighbor...
Automated medical image segmentation is a challenging task that benefits from the use of effective image appearance models. In this paper, we compare appearance models at three reg...
Joshua Stough, Robert E. Broadhurst, Stephen M. Pi...
Fast MR imaging techniques often exploit the redundancy present in an underlying MR image time series to compensate for k-space undersampling. When imaging motion using techniques...
Harsh K. Agarwal, Khaled Z. Abd-Elmoniem, Jerry L....