COLLABORATIVE RESEARCH: ABI Innovation: Shape Analysis for Phenomics with 3D Imaging Data

通过应用高分辨率数字成像方法来非侵入性地可视化复杂的生理特征，比较形态学领域已经发生了革命性的变化。然而，复杂形态特征的真正定量表征和比较仍然不能通过现有方法充分解决，现有方法通常仅针对理想化的2D图像或表面开发。准确和有效的表征和比较的形状与3D噪声成像数据代表高度非平凡的计算问题，尚未得到充分解决的比较形态学研究，也没有有效的计算软件提供给研究人员。该项目的目标是开发先进的计算方法，从高分辨率三维体素为基础的数字成像模式的标本形态的准确定量表征和比较。随着人们越来越认识到来自先进成像方法的生物标本数字图书馆的重要性，例如NSF资助的数字鱼类图书馆（DFL）和数字形态学（DigiMorph）项目，利用这些数据的先进方法非常重要，但也带来了重大的技术挑战。两大类问题是至关重要的：1）从高分辨率体积数据定量表征复杂形态特征的能力和2）标本之间比较这些特征的方法。我们的目标是发展两种具体的几何形态分析计算方法，可以最佳地表征和比较嵌入在真实的3D成像数据中的几何特征，并且对噪声和分辨率限制具有鲁棒性：1）一种新的基于3D图像球面波分解的签名的形状分析方法; 2）提出了一种鲁棒的基于同态图像和界标配准的非线性空间归一化方法。空间归一化方法将允许同源结构正确地非线性地扭曲到彼此或共同模板以进行比较，而分解方法将促进嵌入复杂3D数据集中的形状的鲁棒、高效、准确和自动化表征。然后，这些方法可以用来生成物种特异性的地图集，定义规范的形态，从而促进种间和种内的比较分析。然后将这些方法应用于自动形状分割的一般问题，然后在两个具有重要生物学意义的问题上进行测试：1）短尾负鼠内耳和颅骨的共同进化; 2）三刺鱼从淡水到咸水的进化。（形式、形状或结构）变异是在广泛的生物学科中具有显著影响的问题。用于数字化生物样品的3D体积成像方法的兴起为解决这些问题提供了很大的可能性，但需要一个理论和计算框架，能够使研究人员有效和准确的方法来分析嵌入在3D体积噪声数字数据中的复杂生物结构。该项目的目标是开发计算工具，以解决这些分析的核心的两个主要问题：准确和有效地1）表征复杂的形态特征和2）比较标本之间的形态特征的能力。执行这些操作的能力对于促进所有数字图书馆数据用于定量形态学至关重要，但迄今为止尚未开发。该提案的目标是开发分析软件，以填补数字成像方法与其最终潜力之间的桥梁，通过开发计算方法来解决广泛的形态学问题，告知我们物种进化和多样化的知识，从而改变比较形态学领域。该项目开发的方法将大大扩展研究人员和学生将定量解剖测量纳入进化生物学研究的能力。这些方法是通用的，适用于任何3D成像模式，因此将是任何数字图书馆的实用程序，并将作为一个平台上，新的技术和方法可以在未来的应用。由此产生的分析工具将是开放源码的，并通过DFL网站（http：//www.example.com）向研究人员传播。www.digitalfishlibrary.org将在Cabrillo海洋水族馆举办相应的公众教育展览（http：//www.cabrillomarineaquarium.org/）。开发一个通用的计算平台，从三维数字数据的计算形态学将允许进化生物学家定量和可重复地解决问题，提供更深入的了解生态参数可能是如何，从字面上看，“塑造”生物多样性，从而具有潜在的深远影响进化生物学领域。

The field of comparative morphology has been revolutionized by the application of high resolution digital imaging methods to non-invasively visualize complex physiological features. However, truly quantitative characterization and comparison of complex morphological features still cannot be adequately addressed by existing methods, which are typically developed only for idealized 2D images or surfaces. The accurate and efficient characterization and comparison of shapes with 3D noisy imaging data represents highly non-trivial computational problems which have yet to be adequately addressed in comparative morphology studies, nor has efficient computational software been made available to the researchers. The goal of this project is to develop advanced computational methods for accurate quantitative characterization and comparison of specimen morphology from high resolution 3D voxel-based digital imaging modalities. With the growing recognition of the importance of digital libraries of biological specimens derived from advanced imaging methods, such as the NSF funded Digital Fish Library (DFL) and Digital Morphology (DigiMorph) projects, advanced methods for utilizing these data are of great importance, but pose significant technical challenges. Two broad classes of problems are of critical importance: 1) The ability to quantitatively characterize complicated morphological features from high resolution volumetric data and 2) Methods for comparing such features between specimens. Our objective is to develop two specific computational methods for geometric morphological analysis that can optimally characterize and compare geometric features embedded within real 3D imaging data, and are robust to noise and resolution limitations: 1) A novel shape analysis method based on signatures derived from spherical wave decomposition of 3D images; 2) A robust non-linear spatial normalization method based on diffeomorphic image and landmark registration. The spatial normalization methods will allow homologous structures to be correctly non-linearly warped to each other or a common template for comparison, while the decomposition method will facilitate robust, efficient, accurate, and automated characterization of shapes embedded within complex 3D datasets. These methods can then be used to generate species-specific atlases that define normative morphologies, thus facilitating both inter- and intra-specific comparative analyses. These methods will then be applied to the general problem of automated shape segmentation, then tested on two problems of significant biological importance: 1) Co-evolution of the short-tailed opossum inner ear and cranium and 2) Three-spine stickleback evolution from freshwater to saltwater species.Characterization and comparison of morphological (form, shape, or structure) variations is a problem of significant impact across a wide range of biological disciplines. The rise of 3D volumetric imaging methods for digitizing biological samples offers great possibilities for addressing these issues but requires a theoretical and computational framework capable of allowing researchers efficient and accurate methods for analyzing complicated biological structures embedded within 3D volumetric noisy digital data. The goal of this project is to develop computational tools to address the two primary issues at the heart of these analyses: The ability to accurately and efficiently 1) characterize complex morphological features and 2) compare morphological features between specimens. The ability to perform these is critical to facilitating the use of all digital library data for quantitative morphology but to date have not been developed. The goal of this proposal is to develop analysis software to fill this significantgap in the bridge between digital imaging methods and its ultimate potential for transforming the field of comparative morphology by developing computational methods to address a broad range of morphological questions that inform our knowledge of the evolution and diversification of species. The methods developed by this project will greatly extend the capabilities of researchers and students to incorporate quantitative anatomical measurements into the study of evolutionary biology. The methods are general and applicable to any 3D imaging modality and thus will be of utility to any digital library and will serve as a platform on which new technologies and methodologies can be applied in the future. The resulting analysis tools will be open source and disseminated to researchers through the DFL website (http://www.digitalfishlibrary.org). A corresponding public education exhibit will be developed at the Cabrillo Marine Aquarium (http://www.cabrillomarineaquarium.org/). Developing a general computational platform for the computational morphology from 3D digital data will allow evolutionary biologists to quantitatively and reproducibly address problems that provide greater insight into how ecological parameters might be, quite literally, 'shaping' biodiversity and thus has potentially profound implications for the field of evolutionary biology.