A new approach to kinematic feature extraction from the human right ventricle for classification of hypertension: a feasibility study
Author:
Publisher
IOP Publishing
Subject
Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Reference29 articles.
1. An object-oriented framework for reduced-order models using proper orthogonal decomposition (POD)
2. Generalized finite element method using proper orthogonal decomposition
3. Statistical Analyses of Brain Surfaces Using Gaussian Random Fields on 2-D Manifolds
4. Parametrization of Closed Surfaces for 3-D Shape Description
5. Inverse viscoelastic material characterization using POD reduced-order modeling in acoustic–structure interaction
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