COLLABORATIVE PROPOSAL:ABI DEVELOPMENT: AN INTEGRATED PLATFORM FOR RETRIEVAL, VISUALIZATION AND ANALYSIS OF 3D MORPHOLOGY FROM DIGITAL BIOLOGICAL COLLECTIONS

生物体的解剖结构可以提供关于其对环境的适应、其进化史和系统关系的重要线索。对生物体S形态和功能的形态(定量)研究通常是在自然历史博物馆进行的，直接测量标本。高分辨率3D成像技术(例如，微型计算机断层扫描)为我们提供了前所未有的细节来捕捉生物标本的内部和外部解剖。同样，在线虚拟“收藏”(例如，MorPhoSource)提供了对这些数据集的方便访问，而不需要科学家前往不同的博物馆来收集他们的数据。然而，这些3D数据集的复杂性质使它们对大多数研究人员来说具有挑战性。在这个项目中，我们建议开发一个开源软件来检索和可视化来自在线博物馆的3D生物标本。我们还将为科学家开发工具，以便更容易地测量和分析解剖结构。几何形态计量学方法(GMM)是一套依赖地标来捕捉生物形状和形状的定量分析技术。该项目建议为开源3D-Slicer(Slicer)可视化软件开发一个GMM模块，作为一个集成的工具包，以解决研究人员在处理3D解剖数据时面临的挑战。除了对地标进行人工注释外，该工具包还将提供两种不同类型的半地标方法(用户引导和自动)，以实现对不同研究设计的通用密集空间采样。带注释的地标数据可以在GMM模块中使用通用Procrstes分析(GPA)进行分析。与GPA相关的形状变化可以分解为主要的翘曲，并可以在全3D中可视化。工具包还将提供一个数据聚合器(Specmart)，它将按分类(和其他令牌)查询在线3D标本存储库MorPhoSource，检索并可视化Slicer内的数据。我们将培训学生3D图像分割、分析和可视化的理论和应用，因为它适用于非医学体积成像数据集，以促进对此类数据集的可重复性和高通量分析。该工具包将使用开放源码工具链和软件开发平台(如GIT)作为Slicer的附加程序包进行开发。该模块的稳定版本将通过Slicer的扩展管理器(及其在线门户)分发，文档将托管在他们的网站上。这种开发的开源性质，以及使用Slicer社区现有的基础设施已经存在了15年以上来分发和支持工具包，这意味着该软件将在未来许多年内广泛使用，并可以得到用户社区的支持(并可能扩展)。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The anatomical structure of an organism can provide important clues about its adaptation to its environment, its evolutionary history and its systematic relationships. The morphometric (quantitative) study of the organism?s shape and function is typically conducted at natural history museums, by measuring the specimen directly. High-resolution 3D imaging techniques (e.g., micro computed tomography) provide us to capture the internal and external anatomy of biological specimens in unprecedented detail. Likewise, online virtual "collections" (e.g., MorphoSource) provide a convenient access to these datasets, without requiring scientists to travel to different museums to collect their data. However, the complex nature of these 3D datasets makes them challenging to analyze for most researchers. In this project, we propose to develop an open-source software to retrieve and visualize 3D biological specimens from online museums. We will also develop tools for the scientists to measure and analyze the anatomy more easily. Geometric Morphometrics Methods (GMM) are a set of quantitative analytical techniques that rely on landmarks to capture organismal shape and form. This project proposes to develop a GMM module for open-source 3D-Slicer (Slicer) visualization software as an integrated toolkit to address challenges researchers face working with 3D anatomical data. In addition to manual annotation of landmarks, the toolkit will provide two distinct (user-guided and automated) types of semi-landmarking methods to enable general purpose dense spatial sampling for different study designs. Annotated landmark data can be analyzed in the GMM module using the Generalized Procrustes Analysis (GPA). Shape variation associated with GPA can be decomposed as principal warps and can be visualized in full 3D. Toolkit will also provide a data aggregator (SpecMart) that will query online 3D specimen repository MorphoSource by taxonomy (and other tokens), retrieve and visualize data within Slicer. We will train students in theory and application of 3D image segmentation, analysis and visualization as it applies to nonmedical volumetric imaging datasets to facilitate reproducible and high-throughput analysis of such datasets. The toolkit will be developed as an add-on package to Slicer using open-source toolchains and software development platforms (such as git). The stable versions of the module will be distributed through Extension Manager of Slicer (and its online portal) and documentation will be hosted on their site. The open-source nature of this development and use of the Slicer community's existing infrastructure that has been in existence more than 15 years to distribute and support the toolkit will mean that the software will be widely available for many years to come and can be supported (and potentially expanded) by the user community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.