Free Surfer Development, Maintenance, and Hardening

摘要： 自由冲浪开发、维护和强化 人类大脑的成像在过去十年中经历了爆炸性的增长，主要是通过各种 核磁共振成像的方式。海量的数据需要自动化和强大的分析工具。 Freesurfer(FS，surfer.nmr.mgh.atherard.edu)是用于神经图像分析的优秀工具之一。 FS下载量超过2万次，核心FS稿件被引用3000多次。 FS是许多由NIH资助的大型数据采集项目的分析核心的一部分，例如 人类连接组计划(HCP)、阿尔茨海默病神经成像倡议(ADNI)和 Frammingham心脏研究(FHS)。在所有基于ADNI的出版物中，有三分之一引用了FS。简单地说，大部分 如果没有FS，神经成像领域的创新研究是不可能的。 自1998年开始，FS以提供对T1的详细和自动化的解剖分析而闻名。 加权MRI图像，尤其是皮质表面。然而，FS解剖分析提供了一个 所有脑成像模式的理想衬底，包括功能磁共振成像、扩散磁共振成像、正电子发射计算机断层扫描、光学/近红外光谱、 脑电/脑磁图。FS提供执行这些分析的工具以及与其他分析集成的软件 工具(如SPM、FSL、AFNI)。FS已用于术前计划，甚至在手术室中使用。 一个具有科学广度和基于FS大小的用户的软件包需要显著的 仅仅是维护它就需要付出很大的努力。例如，FS电子邮件列表每年收到大约3000个帖子 年。FS必须进行持续和严格的测试，因为它是神经成像的一个组成部分 基础设施。用户不断要求新的功能和更好的性能。这项提议将 用于开发、维护和强化FS。具体地说，我们将通过以下方式使FS更加健壮 多个医疗设备，而不仅仅是T1。我们将用无监督的分割来代替全脑分割 在多模式设置中同时优化偏置场校正的方法。我们将实施 有助于数据解释的多变量分析工具。我们还将强化和优化FS 代码库。最后，我们将包括一些工具来帮助用户轻松找到FS分析失败的位置。

Abstract: FreeSurfer Development, Maintenance, and Hardening Imaging of the human brain has seen explosive growth in the last decade mainly through the various modalities of MRI. The massive amount of data requires automatic and robust tools for analysis. FreeSurfer (FS, surfer.nmr.mgh.harvard.edu) is one of the preeminent tools used for neuroimage analysis. FS has more than 20,000 downloads, and the core FS manuscripts have been cited more than 3000 times. FS is part of the analysis core for many NIH-funded large-scale data acquisition projects such as the Human Connectome Project (HCP), Alzheimer's Disease Neuroimaging Initiative (ADNI), and Frammingham Heart Study (FHS). One third of all ADNI-based publications cite FS. Simply put, much of the innovative research done in neuroimaging would not be possible without FS. Started in 1998, FS is best known for providing detailed and automated anatomical analysis of T1- weighted MRI images, especially for the cortical surface. However, FS anatomical analysis provides an ideal substrate for all modes of brain imaging including functional MRI, diffusion MRI, PET, optical/NIRS, EEG/MEG. FS provides tools to perform these analyses as well as software to integrate with other analysis tools (eg, SPM, FSL, AFNI). FS has been used for presurgical planning and even in the operating room. A software package with a scientific breadth and user based the size of FS’s requires a significant amount of effort just to maintain it. For example, the FS email list receives approximately 3000 posts a year. FS must be continuously and rigorously tested because it is such an integral part of the neuroimaging infrastructure. Users are constantly requesting new functionality and better performance. This proposal will be used to develop, maintain, and harden FS. Specifically, we will make FS more robust by incorporating multiple modalities instead of just T1. We will replace the whole-brain segmentation with an unsupervised method that simultaneously optimizes bias field correction in a multimodal setting. We will implements multivariate analysis tools to assist in the interpretation of data. We will also harden and optimize the FS code base. Finally, we will include tools to assist the user to easily find where the FS analysis fails.