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Deformation of Member under Multiple Loadings

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When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
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Related Experiment Video

Updated: Sep 20, 2025

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics

Published on: April 16, 2017

Splitting proximate algorithm for deformable image registration based on functions of bounded deformation.

Chen Li¹, Ziwei Nie¹, Xiaoping Yang¹

¹Department of Mathematics, Nanjing University, Nanjing, P.R. China.

Medical Physics

|June 8, 2022

Summary

This summary is machine-generated.

We developed a faster algorithm, SPA (splitting proximate algorithm), to improve deformable image registration using bounded deformation (BD) functions. SPA generates more plausible displacement fields and is less sensitive to noise, overcoming limitations of previous methods.

Keywords:

deformable image registration functions of bounded deformation proximal term

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Last Updated: Sep 20, 2025

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Published on: April 16, 2017

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Area of Science:

Medical Image Analysis
Computational Anatomy

Background:

Deformable image registration is essential for medical image analysis.
Bounded deformation (BD) functions effectively model displacement fields, capturing discontinuities at organ and tissue edges.

Purpose of the Study:

To address limitations of BD functions, including discontinuous fields due to noise and slow gradient descent algorithms.
To introduce a faster algorithm, SPA (splitting proximate algorithm), for improved deformable registration.

Main Methods:

Implemented a variable-splitting scheme within the deformable registration framework.
Incorporated a proximal term into the energy function based on BD functions.

Main Results:

The SPA algorithm efficiently solves the registration model, producing more natural and plausible displacement fields.
Numerical experiments confirmed the algorithm's effectiveness, stability, and robustness to noise.

Conclusions:

The proposed SPA algorithm significantly enhances deformable image registration.
SPA yields plausible deformation fields and demonstrates robustness against image noise.