Non Iterative Methods for 3D SPECT Image Reconstruction

描述(逐字摘自申请者摘要)：单光子发射 计算机断层扫描(SPECT)在现代医学中发挥着越来越重要的作用 用于脑、肝、肾、前列腺和其他器官成像的药物。这个 该项目的总体目标是开发非迭代方法 SPECT中三维图像的准确高效重建 并评价这些方法在临床上的应用。非迭代法 对于SPECT中的图像重建，本质上是计算高效的。 它们在实践中很有吸引力，因为它们避免了困扰其他人的问题 方法：研究方法。最重要的是，它们可以促进封闭的形式：图像的分析 统计和混叠，允许制定战略以实现最优 抑制噪声、走样和其他错误的影响。这项研究 非迭代方法将显著增强SPECT的能力 检测细微病变并准确量化生理参数 研究和临床应用。 这项建议是专门为进一步发展 非迭代、统计最优、计算高效和 三维SPECT中的数值稳健重建方法及其评价 这些方法在临床SPECT研究中，如IN-111 ProstaScint SPECT 前列腺癌的影像检查。我们预计拟议的方法将充分 补偿光子衰减的影响，与距离相关的空间 分辨率和数据噪声。我们将应用由其他公司开发的方法 调查人员以补偿散布。我们相信我们的研究将会 显著增强SPECT检测微小病变的能力 临床应用。拟议研究的具体目标是：(1) 进一步发展理想最优估计的非迭代方法 正弦图，(2)开发自适应和鲁棒滤波方法，(3) 调查和减轻其他误差源的影响，(4) 使用模型研究评估所提出的方法，以及(5)评估 临床研究中提出的方法。

DESCRIPTION (Verbatim from Applicant's Abstract): Single-photon emission computed tomography (SPECT) is playing an increasingly important role in modern medicine for imaging the brain, liver, kidneys, prostate, and other organs. The broad objectives of the project are to develop non-iterative methods for accurate and efficient reconstruction of three-dimensional (3D) images in SPECT and to evaluate these methods in clinical applications. Non-iterative methods for image reconstruction in SPECT are inherently computationally efficient. They are attractive in practice because they avoid problems that plague other methods. Most importantly, they can facilitate a closed-form: analysis of image statistics and aliasing, allowing the development of strategies for optimal suppression of the effects of noise, aliasing, and other errors. The research on non-iterative methods will significantly enhance the ability of SPECT to detect subtle lesions and to quantify accurately physiologic parameters in research and clinical applications. This proposal is intended specifically for further development of non-iterative, statistically optimal, computationally efficient, and numerically robust reconstruction methods in 3D SPECT and for evaluation of these methods in clinical SPECT studies such as In-111 Prostascint SPECT imaging of prostate cancer. We expect that the proposed methods will adequately compensate for the effects of photon attenuation, distance dependent spatial resolution, and data noise. We will apply methods developed by other investigators to compensate for scatter. We believe that our research will significantly strengthen the ability of SPECT for detecting subtle lesions in clinical applications. The specific aims of the proposed research are (1) to fur ther develop non-iterative methods for optimal estimation of the ideal sinogram, (2) to develop adaptive and robust filtering approaches, (3) to investigate and mitigate the effects of additional sources of error, (4) to evaluate the proposed methods using phantom studies, and (5) to evaluate the proposed methods in clinical studies.