• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议> >Regional effects of an MR-based brain PET partial volume correction algorithm: a Zubal phantom study
【24h】

Regional effects of an MR-based brain PET partial volume correction algorithm: a Zubal phantom study

机译：基于MR的大脑PET部分体积校正算法的区域效应：Zubal幻象研究

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Magnetic resonance (MR) based partial volume correction (PVC) compensates for the limited spatial resolution of positron emission tomography (PET) by using higher-resolution MR images to determine the fractional contributions of small anatomic structures to observed voxel activities. The efficacy of a PVC algorithm depends on correct estimation of imager resolution and accurate PET-MR image co-registration. The purpose of this study was to investigate the regional effects of these errors. Simulated PET and segmented MR data were generated using the Zubal MR brain phantom. Structures were classified as gray matter (GM), white matter (WM) or cerebral spinal fluid (CSF) to form a three-compartment segmented MR image. PET images were simulated by assigning known activities to each segmented MR tissue (10:3:1 GM:WM:CSF) and blurring (4 to 12 mm FWHM). With the above two datasets as inputs, the effects of resolution mismatch and misregistration on the corrected GM activity returned by a PVC algorithm were observed. Mean regional gray matter recovery (GMR) was calculated for each GM structure defined by the Zubal phantom. GMR values were then related to structure dimension and location characteristics. Regional GMR variations in the original simulated PET data were nearly eliminated after ideal PVC but resurfaced, although to a lesser extent, when resolution mismatch and misregistration were introduced. Regional GMR error was found to be related to the surface area to volume ratio of the region and the fraction of gray matter of adjacent regions.
机译：基于磁共振（MR）的部分体积校正（PVC）通过使用更高分辨率的MR图像来确定小解剖结构对观察到的体素活动的贡献，从而补偿了正电子发射断层扫描（PET）的有限空间分辨率。 PVC算法的功效取决于对成像器分辨率的正确估计和准确的PET-MR图像共配准。这项研究的目的是调查这些错误的区域影响。使用Zubal MR脑模型生成了模拟的PET和分段MR数据。将结构分为灰质（GM），白质（WM）或脑脊髓液（CSF），以形成三室分割的MR图像。通过将已知活动分配给每个分割的MR组织（10：3：1 GM：WM：CSF）并模糊（4至12 mm FWHM）来模拟PET图像。使用以上两个数据集作为输入，观察到分辨率失配和配准错误对PVC算法返回的校正GM活性的影响。计算Zubal体模定义的每个GM结构的平均区域灰质回收率（GMR）。然后，将GMR值与结构尺寸和位置特征相关。理想的PVC后，原始模拟PET数据中的区域GMR变化几乎被消除，但是当引入分辨率不匹配和配准错误时，表面粗糙度有所减小，尽管程度较小。发现区域GMR误差与该区域的表面积体积比以及相邻区域的灰质分数有关。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号