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Patterns of dementia are known to fall into dissociated but dispersed brain networks, suggesting that the disease is transmitted along neuronal pathways rather than by proximity. This view is supported by neuropathological evidence for "prion-like" transsynaptic transmission of disease agents like misfolded tau and beta amyloid. We mathematically model this(More)
The goal of deconvolution is to recover an image x from its convolution with a known blurring function. This is equivalent to inverting the linear system y = Hx. In this paper, we consider the generalized problem where the system matrix H is an arbitrary nonnegative matrix. Linear inverse problems can be solved by adding a regularization term to impose(More)
Markov Random Fields (MRF’s) are an effective way to impose spatial smoothness in computer vision. We describe an application of MRF’s to a non-traditional but important problem in medical imaging: the reconstruction of MR images from raw fourier data. This can be formulated as a linear inverse problem, where the goal is to find a spatially smooth solution(More)
The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much(More)
Both the size and location of injury in the brain influences the type and severity of cognitive or sensorimotor dysfunction. However, even with advances in MR imaging and analysis, the correspondence between lesion location and clinical deficit remains poorly understood. Here, structural and diffusion images from 14 healthy subjects are used to create(More)
Current radiologic diagnosis of normal pressure hydrocephalus (NPH) requires a subjective judgment of whether lateral ventricular enlargement is disproportionate to cerebral atrophy based on visual inspection of brain images. We investigated whether quantitative measurements of lateral ventricular volume and total cortical thickness (a correlate of cerebral(More)
Existing parallel MRI methods are limited by a fundamental trade-off in that suppressing noise introduces aliasing artifacts. Bayesian methods with an appropriately chosen image prior offer a promising alternative; however, previous methods with spatial priors assume that intensities vary smoothly over the entire image, resulting in blurred edges. Here we(More)
OBJECTIVES Investigating the potential of myelin repair strategies in multiple sclerosis (MS) requires an understanding of myelin dynamics during lesion evolution. The objective of this study is to longitudinally measure myelin water fraction (MWF), an MRI biomarker of myelin, in new MS lesions and to identify factors that influence their subsequent myelin(More)
Quantitative assessment of myelination is important for characterizing tissue damage and evaluating response to therapy in white matter diseases such as multiple sclerosis. Conventional multicomponent T(2) relaxometry based on the two-dimensional (2D) multiecho spin echo sequence is a promising method to measure myelin water fraction, but its clinical(More)
Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted(More)