Development, Optimization and Implementation of New Algorithms for Improving the Resolution of EM, Acoustic and fMRI Reconstructions

提高电磁、声学和功能磁共振成像重建分辨率的新算法的开发、优化和实施

• 批准号: RGPIN-2016-03652
• 负责人: Smith, Michael
• 金额: $ 2.26万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=614528
• 关键词: Development; Optimization; Implementation; New; Algorithms

Many people are familiar with the internal body images available through magnetic resonance (MR) imaging. Unlike photographic images, MR images are not captured directly as an image but must be calculated using a discrete Fourier transform (DFT) algorithm from signals excited from the hydrogen nuclei in the body. It has been said that “There are more DFT algorithms used to analyze signals on any given day than any other algorithm”. This implies “There are many research opportunities available to understand and solve the limitations of DFTs." A basic problem is that a compromise must be made between spatial resolution, the quality of the MR image captured, and time resolution, the ability to track changes such as imaging the moving heart. False information appears in the image which confuses diagnosis. My team has recently combined our own constrained reconstruction for improving spatial resolution with proposed sparse sampling approaches that deliberately time save by gathering less data. Some unexpected preliminary results were found, with some parts of the image improving quality while others became more distorted. We are developing a new post-processing reconstruction process capable of mathematically manipulating the MR signals to produce an image with all parts having the quality to meet diagnosis needs. This requires combining the best parts of many poor quality images -- similar to recent ideas of replacing the bulky (thick), expensive, high-resolution camera lens in mobile phones with software that combines images from many flat, inexpensive, low-resolution lenses. We have identified that our new approach has the capability of improving the capability of a wide range of signal and image reconstruction algorithms: (1) using a sparse array of acoustic sensors to gather intensity and phase information leading to industrial and community noise localization to help with our Community Acoustic Noise which has recently received considerable media attention, (2) improving the low-resolution fMRI images to provide new markers to diagnose Optical Neuritis (ON). ON is often a preliminary stage leading to Multiple Sclerosis; unfortunately common in northern countries such as Canada and (3) improving an industrial real-time lab bench embedded system’s resolution in characterizing magnetic near-field effects measured using a sparse 2D hall-effect sensor array, Developing these algorithms in the laboratory is one thing, but we must be able to apply these algorithms in practical industrial, medical and community situations. We have been following up on the recent movement of successful business (enterprise) “Agile oriented software processes” into reliable embedded system code. The lack of literature has led us to suggest we use our proposed new reconstruction algorithms to undertake systematic investigations into using Agile ideas in a research field; an area with a potential wide audience.

许多人熟悉通过磁共振（MR）成像可获得的内部身体图像。与摄影图像不同，MR图像不直接作为图像捕获，而是必须使用离散傅立叶变换（DFT）算法根据从体内氢核激发的信号来计算。有人说：“在任何给定的一天，用于分析信号的DFT算法比任何其他算法都多”。这意味着“有许多研究机会可以理解和解决DFT的局限性。“一个基本的问题是，必须在空间分辨率（所捕获的MR图像的质量）和时间分辨率（跟踪变化的能力，如对运动的心脏成像）之间做出妥协。图像中出现错误信息，混淆诊断。 我的团队最近结合了我们自己的约束重建来提高空间分辨率，并提出了稀疏采样方法，通过收集更少的数据来节省时间。结果发现了一些意想不到的初步结果，图像的某些部分改善了质量，而其他部分则变得更加扭曲。我们正在开发一种新的后处理重建过程，能够对MR信号进行数学处理，以生成具有满足诊断需求的质量的所有部分的图像。这就需要将许多低质量图像中最好的部分结合起来--类似于最近的想法，即用软件来取代移动的手机中笨重（厚）、昂贵、高分辨率的摄像头透镜，该软件将许多平面、廉价、低分辨率镜头的图像结合起来。 我们已经确定，我们的新方法能够提高各种信号和图像重建算法的能力：（1）利用稀疏的声学传感器阵列收集强度和相位信息，从而确定工业和社区噪音的位置，以帮助我们解决最近受到媒体相当关注的社区噪音问题，（2）改进低分辨率fMRI图像，为视神经炎的诊断提供新的标志物。ON通常是导致多发性硬化症的初始阶段;不幸的是，在诸如加拿大的北方国家中常见，以及（3）提高工业实时实验室工作台嵌入式系统在表征使用稀疏2D霍尔效应传感器阵列测量的磁近场效应时的分辨率， 在实验室中开发这些算法是一回事，但我们必须能够将这些算法应用于实际的工业，医疗和社区情况。我们一直在跟进最近成功的商业（企业）“敏捷导向的软件过程”到可靠的嵌入式系统代码的运动。由于缺乏文献，我们建议使用我们提出的新重建算法，对在研究领域中使用敏捷思想进行系统的调查;这是一个潜在的广泛受众的领域。