Scientific computing in medical image reconstruction

医学图像重建是医学成像的基础，如果没有准确的重建，医学图像包含错误，使诊断困难或不可能。 然而，在医学图像重建中有许多前沿领域是科学计算领域所未触及的。 该提案旨在解决两个令人兴奋的医学图像重建问题，一个在磁共振成像（MRI）中，一个在计算机断层扫描（CT）中。回波内MRI运动校正着眼于如何使用运动跟踪设备与MR扫描仪，以改善图像重建。 患者的运动，如帕金森震颤，可能会破坏用于诊断和分析多发性硬化症，中风和其他脑血管疾病等疾病的敏感图像。 我们建议，智能使用的运动跟踪数据可以补偿的议案。第二个项目涉及便携式CT扫描仪的重建方法的发展。 纳米技术的研究人员正在研究x射线发射器和探测器的灵活阵列。 使用这些阵列，我们预见到一种新的便携式CT扫描仪，可以部署在事故现场。 然而，这些设备有有趣的重建的挑战，必须解决之前的原型可以built.We建议使用科学计算来解决这些挑战。

Medical image reconstruction is the foundation for medical imaging; without accurate reconstruction, medical images contain errors that make diagnosis difficult or impossible.  Yet, there are many frontiers in medical image reconstruction that are untouched by the field of scientific computing.  This proposal aims at addressing two exciting medical image reconstruction issues, one in magnetic resonance imaging (MRI), and one in computed tomography (CT).Intra-echo MRI motion correction looks at ways to use a motion-tracking device with an MR scanner to improve image reconstruction.  Patient motion, such as Parkinsonian tremors, can corrupt the sensitive images that are used to diagnose and analyse ailments like multiple sclerosis, strokes, and other cerebrovascular diseases.  We propose that the intelligent use of motion-tracking data can compensate for that motion.The second project involves the development of reconstruction methods for portable CT scanners.  Researchers in nanotechnology are working on flexible arrays of x-ray emitters and detectors.  Using these arrays, we forsee a new breed of portable CT scanners that can be deployed right at the scene of an accident.  However, these devices have interesting reconstruction challenges that must be addressed before a prototype can be built.We propose the use of scientific computing to address these challenges.