Pengcheng Shi

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Many of the computer vision algorithms have been posed in various forms of differential equations, derived from minimization of specific energy functionals, and the finite element representation and computation have become the de facto numerical strategies for solving these problems. However, for cases where domain mappings between numerical iterations or(More)
We propose a feature-based hierarchical framework for hand geometry recognition, based upon matching of geometrical and shape features. Rid of the needs for pegs, the acquisition of the hand images is simplified and more user-friendly. Geometrical significant landmarks are extracted from the segmented images, and are used for hand alignment and the(More)
We propose and validate the hypothesis that we can use differential shape properties of the myocardial surfaces to recover dense field motion from standard three–dimensional image data (MRI and CT). Quantitative measures of left ventricular regional function can be further inferred from the point correspondence maps. The non-invasive, algorithm–derived(More)
A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, and image analysis efforts on cardiac(More)
The change of BOLD signal relies heavily upon the resting blood volume fraction ([Formula: see text]) associated with regional vasculature. However, existing hemodynamic data assimilation studies pretermit such concern. They simply assign the value in a physiologically plausible range to get over ill-conditioning of the assimilation problem and fail to(More)
Quantitative estimation of nonrigid motion from image sequences has important technical and practical significance. State-space analysis provides powerful and convenient ways to construct and incorporate the physically meaningful system dynamics of an object, the image-derived observations, and the process and measurement noise disturbances. In this paper,(More)
The cardiac physiome model has been proven to be useful for cardiac simulation, and has been more recently utilized to medical image analysis. To perform individualized analysis, structural images are necessary to provide subject-specific cardiac geometries. Although finite element methods have been extensively used for the spatial discretization of the(More)
Bayesian approaches, or maximum a posteriori (MAP) methods, are effective in providing solutions to ill-posed problems in image reconstruction. Based on Bayesian theory, prior information of the target image is imposed on image reconstruction to suppress noise. Conventionally, the information in most of prior models comes from weighted differences between(More)
Personalized noninvasive imaging of subject-specific cardiac electrical activity can guide and improve preventive diagnosis and treatment of cardiac arrhythmia. Compared to body surface potential (BSP) recordings and electrophysiological information reconstructed on heart surfaces, volumetric myocardial transmembrane potential (TMP) dynamics is of greater(More)