Diffusion tensor imaging (DTI) measures, such as fractional anisotropy (FA), and trace are very sensitive to noise contained in the acquired diffusion weighted images. Typical iso...
We propose a novel, fast and robust technique for the computation of anatomical connectivity in the brain. Our approach exploits the information provided by Diffusion Tensor Magne...
Modeling the variability of brain structures is a fundamental problem in the neurosciences. In this paper, we start from a dataset of precisely delineated anatomical structures in ...
Pierre Fillard, Vincent Arsigny, Xavier Pennec, Pa...
Diffusion tensor imaging has accelerated the study of brain connectivity, but single-tensor diffusion models are too simplistic to model fiber crossing and mixing. Hybrid diffusio...
Liang Zhan, Alex D. Leow, Iman Aganj, Christophe L...
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...