Inverse Problems in Medical Imaging: Development and assessment of novel imaging applications for diagnosis and therapy.

医学成像中的逆问题：用于诊断和治疗的新型成像应用的开发和评估。

• 批准号: RGPIN-2017-05503
• 负责人: Pistorius, Stephen
• 金额: $ 2.62万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710732
• 关键词: Inverse; Problems; Medical; Imaging; Development

The research and development of medical imaging systems have played a vital role in improving lives. However, the use of X-ray Computer Tomography (CT) and Positron Emission Tomography (PET) is increasing population dose, organ motion during radiotherapy remains a challenge, and the benefits of advanced technology are often not available to remote communities. The goal of my Discovery program is to research, develop and assess inverse imaging applications to improve image quality, patient safety, therapeutic efficiency or provide approaches that offer improved access for rural communities. This research integrates the physics of radiation transport, Monte Carlo simulation and Dose and Image Reconstruction, with research in Condensed Matter Physics, Expert Systems, Antenna and Sensor Design. Scattered photons can be used to improve the quality of CT, or to reduce the number of projections and dose. For PET, reconstructing images using scattered photons improves the functional image quality for a given dose, and enables anatomic details to be reconstructed. Microwaves can be used to detect small breast lesions in simulated breast phantoms without the risks of x-ray mammography, and megavoltage (MV) imaging can be used to track and predict organ motion. These diverse imaging applications rely on novel algorithms to reconstruct and/or to process the image, to classify the results and to predict outcomes, and all require novel signal sensors (detectors), which push the boundaries of existing technology. Improvements require low noise detectors with high spatial and energy resolution, and for microwave radar systems, a broad frequency bandwidth. My research is approaching these problems from two directions. My collaborators and I are working to develop improved microwave, ultrasound, x-ray and gamma ray detectors for these applications, while my students and I develop improved algorithms which minimize the impact of deficiencies in detector technology, and integrate these new detectors into systems for evaluation. Three themes fall within the current scope of the research. a) The use of novel reconstruction algorithms to image and detect breast tumors from microwave signals detected by a solid-state sensor array, b) The use of realistic data to develop and test scatter enhanced algorithms to reduce dose and improve PET and CT image quality and c) Further development of optical flow and dose calculation algorithms to enable radiation treatment to be optimized when tissue, gantry and field motion is present. My program will provide Medical Physics and Biomedical Engineering training opportunities, education and skills to help develop 26 well-rounded and professional HQP in the NSE, while inventing and evaluating disruptive imaging systems that make use of cutting-edge technology, such as spintronic sensors, multi-layer PET detectors, MV imaging and advanced reconstruction algorithms.

医学成像系统的研究和开发在改善生活方面发挥了至关重要的作用。然而，X射线计算机断层扫描（CT）和正电子发射断层扫描（PET）的使用正在增加人口剂量，放射治疗期间的器官运动仍然是一个挑战，偏远社区往往无法获得先进技术的好处。 我的发现计划的目标是研究，开发和评估逆向成像应用程序，以提高图像质量，患者安全性，治疗效率或提供方法，为农村社区提供更好的访问。本研究整合了辐射传输，蒙特卡罗模拟和剂量和图像重建的物理，在凝聚态物理，专家系统，天线和传感器设计的研究。 散射光子可用于提高CT质量，或减少投影数量和剂量。对于PET，使用散射光子重建图像提高了给定剂量的功能图像质量，并能够重建解剖细节。 微波可用于在模拟乳房模型中检测小的乳房病变，而没有X射线乳房摄影的风险，兆伏（MV）成像可用于跟踪和预测器官运动。这些不同的成像应用依赖于新的算法来重建和/或处理图像，对结果进行分类并预测结果，并且都需要新的信号传感器（检测器），这推动了现有技术的边界。 改进需要具有高空间和能量分辨率的低噪声检测器，并且对于微波雷达系统，需要宽的频率带宽。我的研究从两个方向来探讨这些问题。我和我的合作者正在为这些应用开发改进的微波，超声波，X射线和伽马射线探测器，而我和我的学生开发改进的算法，最大限度地减少探测器技术缺陷的影响，并将这些新的探测器集成到系统中进行评估。 三个主题属于目前的研究范围。a）使用新的重建算法来根据固态传感器阵列检测到的微波信号对乳腺肿瘤进行成像和检测，B）使用真实数据来开发和测试散射增强算法，以减少剂量并提高PET和CT图像质量，以及c）进一步开发光流和剂量计算算法，以使得当存在组织、机架和场运动时能够优化放射治疗。 我的计划将提供医学物理和生物医学工程培训机会，教育和技能，以帮助在NSE中培养26名全面和专业的HQP，同时发明和评估利用尖端技术的破坏性成像系统，如自旋电子传感器，多层PET探测器，MV成像和先进的重建算法。