Learn More
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)
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)
  • Zhuwen Li, Loong-Fah Cheong, Shuoguang Yang, Kim-Chuan Toh
  • 2017
While clustering has been well studied in the past decade, model selection has drawn much less attention due to the difficulty of the problem. In this paper, we address both problems in a joint manner by recovering an ideal affinity tensor from an imperfect input. By taking into account the relationship of the affinities induced by the cluster structures,(More)
In this paper, we explore how a visual system equipped with a pair of frontally-placed eyes/cameras can rapidly estimate egomotion and depths for the task of locomotion by exploiting the eye topography. We eschew the traditional approach of motion-stereo integration , as finding stereo correspondence is a com-putationally expensive operation. Instead, we(More)