A non-rigid registration method for the analysis of local deformations in the wood cell wall

IF 3.56 Q1 Medicine
Alessandra Patera, Stephan Carl, Marco Stampanoni, Dominique Derome, Jan Carmeliet
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引用次数: 10

Abstract

This paper concerns the problem of wood cellular structure image registration. Given the large variability of wood geometry and the important changes in the cellular organization due to moisture sorption, an affine-based image registration technique is not exhaustive to describe the overall hygro-mechanical behaviour of wood at micrometre scales. Additionally, free tools currently available for non-rigid image registration are not suitable for quantifying the structural deformations of complex hierarchical materials such as wood, leading to errors due to misalignment. In this paper, we adapt an existing non-rigid registration model based on B-spline functions to our case study. The so-modified algorithm combines the concept of feature recognition within specific regions locally distributed in the material with an optimization problem. Results show that the method is able to quantify local deformations induced by moisture changes in tomographic images of wood cell wall with high accuracy. The local deformations provide new important insights in characterizing the swelling behaviour of wood at the cell wall level.

Abstract Image

木材细胞壁局部变形分析的非刚性配准方法
本文研究了木质细胞结构图像配准问题。考虑到木材几何形状的巨大可变性以及由于吸湿而导致的细胞组织的重要变化,基于仿射的图像配准技术并不能详尽地描述木材在微米尺度上的整体湿力学行为。此外,目前可用于非刚性图像配准的免费工具不适合量化复杂分层材料(如木材)的结构变形,导致由于不对准而导致的误差。在本文中,我们将现有的基于b样条函数的非刚性配准模型应用于我们的案例研究。改进后的算法将材料局部分布的特定区域内的特征识别概念与优化问题相结合。结果表明,该方法能够较准确地量化木材细胞壁层析图像中水分变化引起的局部变形。局部变形为描述木材在细胞壁水平的膨胀行为提供了新的重要见解。
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来源期刊
Advanced Structural and Chemical Imaging
Advanced Structural and Chemical Imaging Medicine-Radiology, Nuclear Medicine and Imaging
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