Robust Cerebrum and Cerebellum Segmentation for Neuroimage Analysis

用于神经图像分析的稳健大脑和小脑分割

• 批准号: 7708268
• 负责人: Jerry L Prince
• 金额: $ 21.33万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7708268
• 关键词: Algorithms; Atlases; Automatic Data Processing; Biomedical Computing; Brain; Cephalic; Cerebellum; Cerebrum; Classification; Code; Collaborations; Communities; Complement; Computer software; Data; Environment; Excision; Funding; Human; Image; Image Analysis; Java; Knowledge; Laboratories; Magnetic Resonance Imaging; Medical; Methodology; Methods; NIH Program Announcements; Neurosciences; Performance; Process; Reporting; Research; Research Project Grants; Science; Software Engineering; Software Tools; Source Code; Staging; System; Testing; Thick; Tissues; Universities; Weight; Writing; brain volume; computerized data processing; cranium; design; gray matter; image processing; imaging Segmentation; innovation; morphometry; neuroimaging; novel; open source; public health relevance; software development; symposium; tool

DESCRIPTION (provided by applicant): Extraction of the cerebrum and cerebellum from structural magnetic resonance images is an important initial step in neuroimage analysis. Inaccurate brain extraction (also referred to as skull stripping) can have a very negative effect on subsequent analyses, and for some sensitive studies, manually-assisted extraction remains the only viable option. Despite many reported algorithms and several software packages available for research purposes, there is still widespread variability in the performance of these methods, and none are adequate for comprehensive analyses involving the whole human brain and large numbers of studies. This R21 will develop, code, test, and distribute the SPECTRE (Simple Paradigms for Extra Cranial Tissue REmoval) software for the neuroscience community. Funded as an R21 under the Program Announcement PAR-08-183, this Exploratory Collaboration with the NA-MIC National Center for Biomedical Computing, will jointly develop SPECTRE software within the "NA-MIC Kit" software environment and will make it freely available as both source code and platform specific executables. The underlying SPECTRE image processing algorithm was recently developed and validated in the Image Analysis and Community Laboratory (IACL) at Johns Hopkins University and has been reported in a leading conference. SPECTRE is innovative in its use of multiple atlases, its combined use of fuzzy classification, watershed segmentation, and morphological image segmentation, and its emphasis on a high penalty for accidentally removing cortical gray matter. Research and develop efforts will accomplish the following specific aims: 1) The existing code and all new code will be ported and written using the standard NA-MIC software methodology; 2) The algorithms for isolating and establishing a coordinate system on the cerebellum will be completed; 3) The new code will be tested and optimized for differently acquired T1-weighted data; 4) An extensive comparison between SPECTRE and existing algorithms will be carried out. The result will be an algorithm that can take an arbitrary T1-weighted MR brain volume and return a volume containing the cerebellum, the cerebrum, or both, and with coordinate systems automatically established on the cerebrum and cerebellum. The SPECTRE software tool will be the first to provide selective isolation of the cerebrum, the cerebellum, or both. It will also be the first automated method for establishing a coordinate system on the cerebellum. It should be noted that the optimization criteria we have developed is particularly designed for very sensitive studies of brain changes, which has led us to incorporate a very high penalty on erroneous gray matter loss during the isolation step. For this reason and also because the software tool will be very robust, easy to use, and will function within the richly appointed environment of the widely used 3D Slicer software, we expect that the SPECTRE software tool will grow to be very popular within the neuroimaging community. PUBLIC HEALTH RELEVANCE: Many advances in brain science are discovered using magnetic resonance images of the brain. Automatic processing of these data, often involving very large numbers of subjects in any given study, is a necessary component in gaining scientific or medical knowledge, and automatic identification of the brain is typically a key first step in the process. This research project will provide software, freely available to the public that will automatically identify the cerebrum and cerebellum of the human brain so that further analysis, both conventional and potentially novel, can then be carried out.

描述（由申请人提供）：从结构磁共振图像中提取大脑和小脑是神经图像分析的重要第一步。 不准确的大脑提取（也称为头骨剥离）可能会对随后的分析产生非常负面的影响，对于一些敏感的研究，手动辅助提取仍然是唯一可行的选择。 尽管有许多报道的算法和一些用于研究目的的软件包，但这些方法的性能仍然存在广泛的可变性，没有足够的涉及整个人脑和大量研究的全面分析。 该R21将为神经科学社区开发，编码，测试和分发幽灵（用于额外颅骨组织的简单范例）。 这项与NA-MIC国家生物医学计算中心的探索性合作将在计划公告下作为R21资助，将在“ Na-Mic Kit”软件环境中共同开发Specter Software源代码和平台特定的可执行文件。 最近在约翰·霍普金斯大学的图像分析和社区实验室（IACL）中开发和验证了基础幽灵图像处理算法，并在一场领先的会议上进行了报道。 Spectre在使用多个地图酶，模糊分类，分水岭分割和形态图像分割方面具有创新性，以及其强调意外去除皮质灰质物的高惩罚。 研究和开发工作将实现以下特定目的：1）现有代码和所有新代码将使用标准的NA-MIC软件方法进行移植和编写； 2）将完成用于隔离和建立小脑坐标系的算法； 3）新代码将针对不同获得的T1加权数据进行测试和优化； 4）将进行幽灵和现有算法之间的广泛比较。 结果将是一种算法，该算法可以采用任意的T1加权MR脑体积并返回包含大脑，大脑或两者兼而有之的体积，并在大脑和小脑上自动建立了坐标系统。 Specter软件工具将是第一个提供大脑，小脑或两者兼而有之的选择性隔离的工具。 这也将是在小脑上建立坐标系的第一个自动化方法。 应当指出的是，我们开发的优化标准是针对大脑变化非常敏感的研究而设计的，这使我们在隔离步骤中对错误的灰质损失施加了非常高的惩罚。 因此，由于软件工具将非常强大，易于使用，并且在广泛使用的3D SliCer软件的丰富环境中起作用，因此我们希望Specter Software工具在神经影像中会非常流行社区。 公共卫生相关性：使用大脑的磁共振图像发现了脑科学的许多进步。 在任何给定的研究中通常涉及大量受试者的自动处理这些数据是获得科学或医学知识的必要组成部分，并且自动识别大脑通常是该过程的关键第一步。 该研究项目将为公众免费提供软件，这些软件将自动识别人脑的大脑和小脑，以便可以进行进一步的分析，包括常规和潜在的新颖性。