We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications. We transform the problem into a problem of learning with noise by labelin...
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
Cartesian tensor basis have been widely used to approximate spherical functions. In Medical Imaging, tensors of various orders have been used to model the diffusivity function in ...
Angelos Barmpoutis, Baba C. Vemuri, John R. Forder
Several functional and biomedical imaging techniques rely on determining hemodynamic variables and their changes in large vascular networks. To do so at micro-vascular resolution ...