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Quantification and geometric analysis of coiling patterns in gastropod shells based on 3D and 2D image data

机译:基于3D和2D图像数据的加麻壳卷绕图案的量化与几何分析

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The morphology of gastropod shells has been a focus of analyses in ecology and evolution. It has recently emerged as an important issue in developmental biology, thanks to recent advancements in molecular biological techniques. The growing tube model is a theoretical morphological model for describing various coiling patterns of molluscan shells, and it is a useful theoretical tool to relate local tissue growth with global shell morphology. However, the growing tube model has rarely been adopted in empirical research owing to the difficulty in estimating the parameters of the model from morphological data. In this article, I solve this problem by developing methods of parameter estimation when (1) 3D Computed Tomography (CT) data are available and (2) only 2D image data (such as photographs) are available. When 3D CT data are available, the parameters can be estimated by fitting an analytical solution of the growing tube model to the data. When only 2D image data are available, we first fit Raup's model to the 2D image data and then convert the parameters of Raup's model to those of the growing tube model. To illustrate the use of these methods, I apply them to data generated by a computer simulation of the model. Both methods work well, except when shells grow without coiling. I also demonstrate the effectiveness of the methods by applying the model to actual 3D CT data and 2D image data of land snails. I conclude that the method proposed in this article can reconstruct the coiling pattern from observed data. (C) 2014 Elsevier Ltd. All rights reserved.
机译:加麻壳的形态一直是生态和演化中分析的重点。由于最近分子生物技术的进展,它最近成为发展生物学中的一个重要问题。生长管模型是用于描述软体动物壳的各种卷绕模式的理论形态学模型,是将局部组织生长与全球壳形态相关的有用理论工具。然而,由于难以从形态数据估计模型的参数,因此在实证研究中,越来越多的管模型很少采用。在本文中,我通过开发参数估计方法来解决这个问题,当(1)3D计算断层扫描(CT)数据可用并且(2)仅有2D图像数据(例如照片)时。当3D CT数据可用时,可以通过将生长管模型的分析解决方案拟合到数据来估计参数。当只有2D图像数据可用时,我们首先将Raup的模型适合2D图像数据,然后将Raup模型的参数转换为生长管模型的型号。为了说明这些方法的使用,我将它们应用于模型的计算机模拟生成的数据。两种方法都很好地工作,除非贝壳没有卷积时。我还通过将模型应用于陆蜗牛的实际3D CT数据和2D图像数据来证明这些方法的有效性。我得出结论,本文提出的方法可以重建来自观察到的数据的卷绕模式。 (c)2014年elestvier有限公司保留所有权利。

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