Shuisheng Xie

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Computing the average anatomy and measuring the anatomical variability within a group of subjects are common practices in Computational Anatomy. In this paper, we propose a statistical analysis framework for 2D/3D shapes. At the core of the framework is a parametric shape representation formulated as a concatenation of skeleton points and the discs centered(More)
Comparing different shapes is a fundamental problem in Computational Anatomy (CA), where a rigorous and intrinsic distance metric is key for a shape analysis system to work effectively and consistently. In this paper, we propose a shape comparison and classification framework that consists of two major components. A meridian-based shape representation,(More)
Repair and regeneration of injured peripheral nerves have always been a focus in the field of orthopedics. Traditional nerve atlas contains only two-dimensional information and canpsilat display the real cross and recombination process of nerve bundles in its whole length. To solve this problem, a system, 3D nerve, is proposed for the 3D reconstruction of(More)
Computing the average anatomy and measuring the anatomical variability within a group of subjects are common practices in Computational Anatomy. In this paper, we propose an information rich shape representation based on curve skeletons. Our method starts with the extraction of curve skeletons of the input shape, followed by fitting the object boundary with(More)
One of the common practices in obesity and diabetes studies is to measure the volumes and weights of various adipose tissues, among which, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) play critical yet different physiological roles in mouse aging. In this paper, a robust two-stage VAT/SAT separation framework for micro-CT mouse data(More)
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