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This paper describes a method developed to assist in the detection and reconstruction of the human upper airway using cone beam computed tomography (CBCT) image slices and a three dimensional (3D) Gaussian kernel blurring filter. The segmented airway is characterized by the corresponding three principal axes that are selected for viewing direction orientation via rotation and translation. The aforementioned...
A statistical interpretation of existing parallel magnetic resonance imaging methods reveals that simple least squares or Tikhonov regularization methods are unable to completely remove aliasing and noise from parallel MRI data during reconstruction. We present a Bayesian framework called EPIGRAM which overcomes these problems by introducing powerful edge-preserving spatial coherence priors. We show...
A statistical interpretation of existing parallel magnetic resonance imaging methods reveals that the underlying noise model is of additive independent Gaussian noise. In reality MR imaging processes suffer from a variety of noise, errors and other uncertainties. A careful statistical analysis of these uncertainties can potentially allow significant improvement of the reconstruction process. In this...
High resolution 3D coronary artery MR angiography is time-consuming and can benefit from accelerated data acquisition provided by parallel imaging techniques without sacrificing spatial resolution. Currently, popular maximum likelihood based parallel imaging reconstruction techniques such as the SENSE algorithm offer this advantage at the cost of reduced signal-to-noise ratio (SNR). Maximum a posteriori...
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