ShapeWorksStudio: An Integrative, User-Friendly, and Scalable Suite for Shape Representation and Analysis

项目摘要 解剖结构的形态(或形状)构成了临床医生的共同语言，其中ab. 解剖形态的正常往往与有害的功能有关。虽然这些观察结果通常是有质量的- 预测，fi和微妙的，定量的形状效果需要应用数学，统计学和计算 将解剖学解析成数字表示，这将有助于生物相关假说的测试。 基于粒子的形状建模(PSM)及其相关的软件工具套件ShapeWorks使学习成为可能 通过在图像段上自动密集放置同源地标来表示种群级别的形状 具有任意拓扑学的普通解剖学指导。ShapeWorks的实用程序已在 生物医学应用的范围。尽管它对研究企业有明显的效用，而且高度允许 开放源码许可，由于固有的权衡，ShapeWorks没有可行的商业化道路 在开发和维护成本之间，以及专业的科学fic和临床市场之间。ShapeWorks拥有 有可能改变研究人员处理解剖形态研究的方式，但它的广泛应用-- 医学和生物学的可复制性受到几个障碍的阻碍，大多数现有的形状建模包 脸。最重要的障碍是(1)现有形状建模的复杂性和陡峭的学习曲线 流水线及其增加的计算和计算机内存需求；(2)相当专业的知识， 分割感兴趣的解剖以进行统计分析所需的时间和精力；以及(3)缺乏可互操作 可以很容易地整合到生物医学研究实验室的实现。在这个项目中，我们支持- Ppose ShapeWorksStudio，这是一款利用ShapeWorks实现自动化人群/患者级别的软件套件 解剖形状的建模，以及广泛使用的可视化和处理体积的开源工具Seg3D- RIC图像-用于fl可执行的手动/半自动分割和交互式手动校正分割 解剖学。在目标1中，我们将在一个框架中集成ShapeWorks和Seg3D，该框架支持大数据队列 使用户能够以直截了当的方式透明地从图像数据到形状模型。在目标2中， 我们将赋予Seg3D一种机器学习方法，在统计中提供自动分割- CAL框架，将图像数据与ShapeWorks提供的特定于人群的fic形状先验相结合。在AIM 3、我们将支持与现有开源软件包和工具包的互操作性，并提供绑定 到生物医学研究社区中常用的编程语言。为了促进可再生性， 我们将开发和发布标准工作fl操作系统和特定领域的fic测试用例。该项目结合了一个 跨学科研发团队，在统计分析和图像方面拥有数十年的经验 理解和应用程序科学家说服fiRM，建议的开发对 生物医学和临床研究社区。我们的长期目标是使ShapeWorks成为 医学中的形状分析，以及本文提出的工作将为实现这一目标奠定基础。

Project Summary The morphology (or shape) of anatomical structures forms the common language among clinicians, where ab- normalities in anatomical shapes are often tied to deleterious function. While these observations are often quali- tative, finding subtle, quantitative shape effects requires the application of mathematics, statistics, and computing to parse the anatomy into a numerical representation that will facilitate testing of biologically relevant hypotheses. Particle-based shape modeling (PSM) and its associated suite of software tools, ShapeWorks, enable learning population-level shape representation via automatic dense placement of homologous landmarks on image seg- mentations of general anatomy with arbitrary topology. The utility of ShapeWorks has been demonstrated in a range of biomedical applications. Despite its obvious utility for the research enterprise and highly permissive open-source license, ShapeWorks does not have a viable commercialization path due to the inherent trade-off between development and maintenance costs, and a specialized scientific and clinical market. ShapeWorks has the potential to transform the way researchers approach studies of anatomical forms, but its widespread ap- plicability to medicine and biology is hindered by several barriers that most existing shape modeling packages face. The most important roadblocks are (1) the complexity and steep learning curve of existing shape modeling pipelines and their increased computational and computer memory requirements; (2) the considerable expertise, time, and effort required to segment anatomies of interest for statistical analyses; and (3) the lack of interoperable implementations that can be readily incorporated into biomedical research laboratories. In this project, we pro- pose ShapeWorksStudio, a software suite that leverages ShapeWorks for the automated population-/patient-level modeling of anatomical shapes, and Seg3D – a widely used open-source tool to visualize and process volumet- ric images – for flexible manual/semiautomatic segmentation and interactive manual correction of segmented anatomy. In Aim 1, we will integrate ShapeWorks and Seg3D in a framework that supports big data cohorts to enable users to transparently proceed from image data to shape models in a straightforward manner. In Aim 2, we will endow Seg3D with a machine learning approach that provides automated segmentations within a statisti- cal framework that combines image data with population-specific shape priors provided by ShapeWorks. In Aim 3, we will support interoperability with existing open-source software packages and toolkits, and provide bindings to commonly used programming languages in the biomedical research community. To promote reproducibility, we will develop and disseminate standard workflows and domain-specific test cases. This project combines an interdisciplinary research and development team with decades of experience in statistical analysis and image understanding, and application scientists to confirm that the proposed developments have a real impact on the biomedical and clinical research communities. Our long-term goal is to make ShapeWorks a standard tool for shape analyses in medicine, and the work proposed herein will establish the groundwork for achieving this goal.