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The assessment of tissue perfusion by dynamic contrast-enhanced (DCE) imaging involves a deconvolution process. For analysis of DCE imaging data, we implemented a regression approach to select appropriate regularization parameters for deconvolution using the standard and generalized singular value decomposition methods. Monte Carlo simulation experiments… (More)
PURPOSE Hemorrhagic transformation (HT) is a common consequence of infarction independent of thrombolytic therapy. Our purpose was to examine if permeability imaging in admission perfusion CT data of patients with acute stroke might indicate a subsequent HT by imaging the disrupted permeability barriers between blood and brain. MATERIALS AND METHODS A… (More)
This short communication presents significantly increased permeability in two patients with acute stroke, indicating an early blood-brain barrier disruption. Neither of the patients had undergone any thrombolytic therapy and hemorrhaged later. Increased permeability was assessed in both patients using a distributed-parameter model of capillary-tissue… (More)
We investigated the ability of monocular human observer to scale absolute distance during sagittal head motion in the presence of pure optic flow information. Subjects were presented at eye-level computer-generated spheres (covered with randomly distributed dots) placed at several distances. We compared the condition of self-motion (SM) versus object-motion… (More)
We present two regression models for the automatic estimation of bolus arrival times (BATs) in dynamic contrast MRI datasets. Results of Monte Carlo simulation experiments show that the means and standard deviations of the estimated BATs are within the sampling interval even in the presence of significant noise.
Quantitative estimates of physiological parameters associated with cerebral blood flow can be derived from the analysis of dynamic contrast-enhanced (DCE) images, using an appropriate model of the underlying tissue impulse residue function. The theoretical formulation of a distributed parameter model of tissue microcirculation, which accounts for the… (More)
Dynamic contrast-enhanced (DCE) imaging using MRI or CT is emerging as a promising tool for diagnostic imaging of cerebral disorders and the monitoring of tumor response to treatment. In this study, we present a robust and efficient deconvolution method based on a linearized model of the impulse residue function, which allows for the mapping of functional… (More)
Time-To-Collision (TTC) is a common vision feature used to avoid obstacles, and is frequently used in cinematography to induce emotional effects. In this paper, we show how TTC can lead to several high-level video categories. The extracted TTC shots (low-level feature) are mapped to their corresponding high-level indices. The information conveyed by… (More)
The majority of benign, non-parasitic liver cysts are asymptomatic. Surgical treatment is reserved for symptomatic patients and frequently involves partial excision or marsupialization via a laparotomy. Surgery is occasionally offered for asymptomatic large cysts, where complications of cyst rupture, intra-cystic bleeding and infection are more common. The… (More)
Computer vision and machine learning, currently focusing on clustering, labeling, motion analysis and structure recovery of complex scenes.