Image acquisition and analysis tools for magnetic resonance imaging near brain injury

在接受过手术或脑损伤的患者中，在损伤周围区域获取的磁共振成像(MRI)数据中可能存在失真或伪影。在磁共振成像中，射频电磁脉冲被用来激发来自样本的信号，以千赫频率切换的电磁场梯度脉冲被用来告诉我们该信号来自样本中的哪里，从而允许创建图像。这两种形式的电磁脉冲结合在一起，形成了称为脉冲序列的工具。在获取MRI数据后，可以重建出细节图像。可以创建新的脉冲序列以最小化伪影并从样本中提取唯一信息。在数据采集之后，可以开发组合由多个脉冲序列获得的信息以提取特征并分离从单个成像序列获得的数据中不可见的结构的模型和图像处理工具。 本课程侧重于磁共振物理学研究的两个领域。 1)研究和开发能够最小化伪影和失真的脉冲序列；以及 2)开发和测试图像分析工具，这些工具可能有助于可视化通常难以分析的大脑区域。 脉冲序列：我的研究旨在研究新的脉冲序列设计，它可以最大限度地减少技术挑战，并在通常受伪影破坏的环境中促进改进MRI。这项工作的目标是通过开发新的脉冲序列来解决成像限制，该序列结合了加速数据收集策略和优化的信号激励和采集策略，加速数据收集策略使我们能够同时从样本的多个区域进行采集，而优化信号激励和采集策略使我们能够最大限度地减少延迟引起的图像失真。 图像处理方法：大多数结构分割工具依赖于现有的脑图谱以及成像序列，这些序列的对比度可能会因意外材料的存在而改变。我们将创建改进分割的工具，并能够结合来自不同MRI序列的信息，包括正在开发的新序列。我们将仔细质疑和测试我们的模型和结果，以减少或消除偏差，并使用我们的分析结果来指导脉冲序列设计。 通过这项工作，我打算培养一批不同的研究生和本科生。我将利用我在科学推广方面的经验，通过积极鼓励来自不同背景的候选人来补充被动和部门招聘。 能够有效地评估传统上因伪影而难以成像的样本，将扩大这一强大工具的实用范围，包括原本无法获得信息丰富的MRI检查的患者。

In patients who have had surgery or brain injuries there may be distortions or artifacts in the magnetic resonance imaging (MRI) data acquired in the region surrounding the injury. In MRI, radio frequency electromagnetic pulses are used to excite a signal from the sample and electromagnetic field gradient pulses, switched at kilohertz frequencies are used to tell us where in the sample that signal is coming from allowing the creation of an image. Combined, these two forms of electromagnetic pulses create tools called pulse sequences. After the acquisition of MRI data, a detailed image can be reconstructed. Novel pulse sequences can be created to minimize artifacts and extract unique information from the sample. After data acquisition, it is possible to develop models and image processing tools which combine the information obtained by multiple pulse sequences to extract features and isolate structures not visible in the data obtained from a single imaging sequence. This program focuses two areas of MR physics research 1) Investigating and developing pulse sequences which are capable of minimizing artifacts and distortions; and 2) Developing and testing image-analysis tools which may aid in the visualization of regions of the brain that are typically difficult to analyze. Pulse Sequence: My research aims to investigate new pulse sequence designs which can minimize technical challenges and facilitate improved MRI in environments typically corrupted by artifacts. The goal of this work is to address imaging limitations through the development of new pulse sequences that couple accelerated data collection strategies, which allow us to acquire from multiple regions of the sample simultaneously, and optimized signal excitation and acquisition strategies, which allow us to minimize delay-induced image distortions. Image processing methodology: Most structural segmentation tools rely on existing brain atlases as well as imaging sequences whose contrasts may be changed by the presence of unexpected materials. We will create tools which improve segmentation and are capable of combining information from different MRI sequences, including novel ones under development. We will carefully question and test our models and results to reduce or eliminate bias and use the results of our analysis to inform pulse sequence design. Through this work I intend to train a diverse group of graduate and undergraduate students. I will leverage my experience in science outreach to supplement passive and departmental recruitment by actively encourage candidates from a range of backgrounds. The ability to effectively evaluate samples which are traditionally difficult to image due to artifacts will extend the utility of this powerful tool to include patients who would otherwise be unable to access informative MRI exams.