We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...
We propose a computational framework for learning predictive image features as “biomarkers” for Alzheimer’s Disease discrimination using high-resolutionMagnetic Resonance (M...
Yanxi Liu, Leonid Teverovskiy, Oscar L. Lopez, How...
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...
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...
Image analysis is still considered as the bottleneck in 2D-gel based expression proteomics analysis for biomarkers discovery. We are presenting a new end-to-end image analysis pip...