8 citations · 9 across the 5 of their papers we have counts for
5 papers
Fitting Skeletal Models via Graph-based Learning
Nicolás Gaggion, Enzo Ferrante, Beatriz Paniagua +1
Skeletonization is a popular shape analysis technique that models an object's interior as opposed to just its boundary. Fitting template-based skeletal models is a time-consuming p…
Interior Object Geometry via Fitted Frames
Stephen M. Pizer, Zhiyuan Liu, Junjie Zhao +6
We propose a means of computing fitted frames on the boundary and in the interior of objects and using them to provide the basis for producing geometric features from them that are…
Geodesic-based Predictive Shape Modeling of the Right Ventricle in Patients with Hypoplastic Left Heart Syndrome
Ye Han, James Fishbaugh, Jared Vicory +9
Hypoplastic left heart syndrome (HLHS) is characterized by severe underdevelopment of left ventricle requiring staged surgical reconstruction (stages) to allow the right ventricle…
ORMIR_XCT: A Python package for high resolution peripheral quantitative computed tomography image processing
Michael T. Kuczynski, Nathan J. Neeteson, Kathryn S. Stok +9
High resolution peripheral quantitative computed tomography (HR-pQCT) is an imaging technique capable of imaging trabecular bone in-vivo. HR-pQCT has a wide range of applications,…
Skeletal Point Representations with Geometric Deep Learning
Ninad Khargonkar, Beatriz Paniagua, Jared Vicory
Skeletonization has been a popular shape analysis technique that models both the interior and exterior of an object. Existing template-based calculations of skeletal models from an…