A METHOD FOR DE-SCALPING HUMAN BRAIN MRI DATA USING LIPID RATIO MAP

一种使用脂质比率图去除人脑 MRI 数据的方法

• 批准号: 8169081
• 负责人: ARI BORTHAKUR
• 金额: $ 3.47万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8169081
• 关键词: Algorithms; Area; Brain; Clinical; Computer Retrieval of Information on Scientific Projects Database; Data; Funding; Grant; Human; Image; Imagery; Institution; Lipids; Magnetic Resonance Imaging; Maps; Methods; Perfusion; Process; Publishing; Research; Research Personnel; Resources; Scalp structure; Source; Surface; Techniques; United States National Institutes of Health; base; brain tissue; image registration; interest

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. De-scalping the brain is a very critical step in MRI data post-processing and analyzing. Most common areas of application are visualization, surface rendering, image registration, DTI and perfusion MRI data post-processing, and decreasing the complexity of subsequent processing algorithms. Many applications related to brain MRI either require, or benefits from the ability to accurately segment brain from the non-brain tissue. De-scalping is one of the interesting and challenging problems in MRI and a number of techniques have been developed for accomplishing it. A recent study published by Fennema-Notestine et al. (2006) concluded that existing algorithms had both strengths and weaknesses, but that no single algorithm was robust enough across different sequences. There is still a need for simple and robust methods for accurate de-scalping. Here we present a new simple technique for brain de-scalping. This technique is based upon lipid ratio map computed using with and without lipid saturation images, which are routinely acquired on most of the clinical scanners.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 大脑去头皮是MRI数据后处理和分析中非常关键的一步。最常见 应用领域包括可视化、表面绘制、图像配准、DTI和灌注MRI 数据后处理，降低后续处理算法的复杂度。许多 与脑MRI相关的应用需要或受益于准确分割的能力， 大脑和非大脑组织去头皮是一个有趣的和具有挑战性的问题， 磁共振成像和一些技术已经开发出来，以实现它。 Fennema-Notestine等人（2006年）得出的结论是，现有的算法既有优势， 但是没有一个算法在不同的序列中足够强大。 有 仍然需要用于精确去头皮的简单且鲁棒的方法。在这里，我们提出了一个新的简单的 大脑剥头皮技术 该技术基于使用以下公式计算的脂质比率图： 并且没有在大多数临床扫描仪上常规获取的脂质饱和图像。