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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)
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)
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)
CVPR 2006, contained a serious error. The authors inadvertently did not acknowledge Vladimir Kolmogorov for a significant contribution: in early 2005, he introduced the 1984 construction of Hammer et al. into computer vision, and explained it to us. For a very clear description of the Hammer et al. construction, see: V. Kolmogorov and C. Rother, "(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)
It is well known that gray matter changes occur in neurodegenerative diseases like Alzheimer's (AD) and fronto-temporal dementia (FTD), and several studies have investigated their respective patterns of atrophy progression. Recent work, however, has revealed that diffusion MRI that is able to detect white matter integrity changes may be an earlier or more(More)
The brain's myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret(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)
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)
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)