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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 e x-tracted from the segmented images, and are used for hand alignment and the(More)
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)
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)
We explore filled pause usage in spontaneous medical narration. Expert physicians viewed images of dermatological conditions and provided a description while working toward a diagnosis. The narratives were analyzed for differences in filled pauses used by attending (experienced) and resident (in-training) physicians and by male and female physicians.(More)
Non–rigid motion estimation from image sequences is essential in analyzing and understanding the dynamic behaviors of physical objects. One important example is the dense field motion analysis of the cardiac wall, which could potentially help to better understand the physiological processes associated with heart disease and to provide improvement in patient(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)
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)