DIGITAL IMAGE REPRESENTATIONS FOR TOMOGRAPHIC RADIOLOGY

断层放射学的数字图像表示

• 批准号: 2414217
• 负责人: ROBERT M LEWITT
• 金额: $ 22.88万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-04-01 至 1999-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2414217
• 关键词: artificial intelligence; computer simulation; computer system design /evaluation; digital imaging; model design /development; phantom model; positron emission tomography

This proposal is directed toward improving tomographic imaging in diagnostic radiology and nuclear medicine. It is predicated on the claim that significant advances will be achieved in the fidelity of the images that are reconstructed from the raw detector measurements of the tomographic scanner by changing the basic elements (called "basis functions") with which the image is built in the computer. The conventional basic elements for computerized tomographic imaging are the voxel basis functions, and the sinusoidal basis functions of Fourier analysis. Two classes of promising new basis functions have been developed: functions that are localized in space (as are the voxel basis functions), and functions that are not localized (similar in many respects to sinusoids). The new classes of basis functions are well-suited to constructing faithful digital image representations of the biological structures that have influenced the raw tomographic scanner data. The new localized basis functions have a number of very desirable properties not shared by voxels: they are rotationally symmetric, their Fourier transforms are effectively localized, and they have continuous derivatives of any desired order. The new non-localized basis functions are designed to perform a spatially-variant filtering operation that is required by a non-iterative method of 3D image reconstruction developed by the Principal Investigator. The specific aims are to develop mathematical theory, efficient computer algorithms, application-specific implementations and evaluation criteria for (1) methods of iterative reconstruction from projections, (2) methods of estimating the fundamental limits on the performance of the reconstruction process, and (3) methods of non-iterative 3D reconstruction from projections. For specified imaging tasks, the level of statistical significance will be found for rejection of the null hypothesis that two methods perform a task equally well, in favor of the alternative hypothesis that one method performs the task better. The basis functions of the image representation are the essential core of all methods for computerized image reconstruction, irrespective of the medical imaging modality (e.g., CT, PET, SPECT, MRI). The development of new computer algorithms and their associated image representations will enable the full potential of scanners for functional imaging in emission tomography (PET and SPECT) to be realized by extracting as much information as possible from fully-3D low-statistics projection data.

这项建议旨在改进 诊断放射学和核医学。它是以索赔为前提的 将在图像的保真度方面取得重大进展 它们是从原始探测器的测量结果中重建的 层析扫描仪通过改变基本元素(称为“基础”) 函数“)，用来在计算机中构建图像。 用于计算机化断层成像的常规基本元素是 体素基函数和傅里叶的正弦基函数 分析。给出了两类有前途的新基函数 已开发：在空间中定位的函数(与体素基础一样 函数)和未本地化的函数(在许多方面相似 到正弦波)。新的基函数类非常适合于 构建逼真的生物数字图像表示法 影响原始断层扫描仪数据的结构。新的 局部化基函数具有许多非常理想的性质，而不是 由体素共享：它们是旋转对称的，它们的傅立叶 变换实际上是局部化的，并且它们具有连续的导数 任何想要的顺序。设计了新的非局域基函数 对象所需的空间可变过滤操作。 校长提出的三维图像重建的非迭代方法 调查员。 具体目标是发展数学理论，高效的计算机 算法、特定于应用的实现和评估标准 对于(1)由投影迭代重建的方法，(2)方法 对性能的基本限制进行估计 重建过程；(3)非迭代三维重建方法 从投射中。对于指定的成像任务，统计级别 将发现拒绝零假设的意义，即两个 方法同样能很好地执行任务，而不是使用替代方法 假设有一种方法能更好地完成任务。 图像表示的基函数是图像表示的基本核心 所有用于计算机图像重建的方法，而不考虑 医学成像模式(例如，CT、PET、SPECT、MRI)。的发展。 新的计算机算法及其相关的图像表示将 充分发挥扫描仪在发射方面的功能成像潜力 层析成像(PET和SPECT)将通过尽可能多的提取实现 从全3D低统计投影数据获得尽可能多的信息。