Super-Resolution PET Using Stepping of a Deliberately Misaligned Bed
使用故意错位床的步进进行超分辨率 PET
基本信息
- 批准号:8698748
- 负责人:
- 金额:$ 23.28万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-07-15 至 2016-06-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAnimalsBedsBiological ModelsBrainCharacteristicsClinicalCodeComputer softwareCouplesDataDropsEvaluationEvolutionFutureImageLaboratoriesLesionManufacturer NameMeasuresMechanicsMethodsMetricModelingMorphologic artifactsMotionMotorMovementNoisePatientsPatternPositioning AttributePositron-Emission TomographyRadialRecoveryRelative (related person)ResearchResolutionSamplingScanningSideSignal TransductionSimulateSolutionsStructureSystemTechniquesTestingTimeVendorbody systemclinically relevantcostdata acquisitiondesigndetectorimprovednovelpre-clinicalpublic health relevancereconstructionresponseretinal rodssimulationstatisticswasting
项目摘要
DESCRIPTION (provided by applicant): The objective of this proposal is to test two hypotheses of the imaging characteristics of positron emission tomography (PET): (1) that substantial improvements in reconstruction accuracy can be obtained for whole-body PET systems by super-sampling voxels during acquisition through the near-continuous motion of the patient bed along a direction intentionally - but carefully and accurately - misaligned with respect to the scanner's axial direction; and (2) that super-sampling will allow resolution improvement with iterative algorithms using resolution-recovery techniques, beyond what those algorithms can achieve without super-sampling. Super-resolution through wobbling is a technique historically used in early brain PET systems to improve the sampling, which would typically improve resolution and reduce artifacts. With the introduction of block detectors and whole-body systems, wobbling disappeared because its mechanical cumbersomeness and added expense were not justified since the impact on reconstruction was negligible. This is because the block detectors greatly reduced the crystal size, reducing the importance of crystal size on overall system resolution in comparison with other effects such as acolinearity and signal distortions in readout. Thus, the sampling improved disproportionately to the resolution. Two significant changes have occurred since wobbling was removed from scanners: (1) 3D acquisitions greatly increased the count statistics, which supports the accurate reconstruction of smaller features; and (2) resolution-recovery iterative algorithms have become commonplace. We believe that improving sampling will result in increased accuracy and resolution of modern reconstructions while artifacts will be reduced because resolutions are once again becoming better in comparison to the sampling. We propose a novel method for increasing sampling, including axial sampling, that does not require additional hardware, making the solution possibly attractive to vendors for future systems and as low-cost upgrades to existing systems, if the hypotheses of this proposal are confirmed. The method introduces a small angle in the bed alignment combined with the use of existing bed motors to super-sample the object, requiring no additional scan time. When the bed moves axially, a small transaxial shift results. The specific aims of this proposal include: (i) determining through simulation the optimal stepping pattern and bed-alignment angle; (ii) modifying existing reconstruction software to incorporate the bed-position information; and (iii) experimentally test the method on a TOF research scanner, LaPET, that is in our laboratory. These aims will allow us to fully address the hypotheses of this proposal.
描述(由申请人提供):本提案的目的是测试正电子发射断层扫描(PET)成像特性的两个假设:(1)通过在采集过程中通过患者床沿着一个方向的近连续运动进行超采样体素,可以获得全身PET系统重建精度的实质性提高-但要小心和准确-相对于扫描仪的轴向不对齐;(2)超级采样将允许使用分辨率恢复技术的迭代算法提高分辨率,而这些算法在没有超级采样的情况下无法实现。通过摆动实现超分辨率是一种历史上用于早期脑PET系统的技术,用于改善采样,这通常会提高分辨率并减少伪影。随着块探测器和全身系统的引入,摇晃消失了,因为它的机械繁琐和增加的费用是不合理的,因为对重建的影响可以忽略不计。这是因为块探测器大大减小了晶体尺寸,与读出中的非共线性和信号失真等其他影响相比,降低了晶体尺寸对整体系统分辨率的重要性。因此,采样改善不成比例的分辨率。自扫描仪消除抖动以来,发生了两个重大变化:(1)3D采集大大增加了计数统计,这支持较小特征的准确重建;(2)分辨率恢复迭代算法已经变得司空见惯。我们相信,改进采样将提高现代重建的精度和分辨率,同时减少人工制品,因为与采样相比,分辨率再次变得更好。我们提出了一种增加采样的新方法,包括轴向采样,不需要额外的硬件,使解决方案可能对未来系统的供应商有吸引力,并且作为现有系统的低成本升级,如果这个提议的假设得到证实。该方法在床对准中引入了一个小角度,结合使用现有的床电机对物体进行超采样,不需要额外的扫描时间。当床层轴向移动时,产生一个小的跨轴位移。该方案的具体目标包括:(1)通过仿真确定最佳步进模式和床层对准角度;(ii)修改现有重建软件以纳入床位信息;(iii)在我们实验室的TOF研究扫描仪LaPET上对该方法进行实验测试。这些目标将使我们能够充分处理这项建议的假设。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
SCOTT DEAN METZLER其他文献
SCOTT DEAN METZLER的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('SCOTT DEAN METZLER', 18)}}的其他基金
Quantitative MicroSPECT Imaging of Myocardial Blood Flow in Mice
小鼠心肌血流的定量 MicroSPECT 成像
- 批准号:
10219352 - 财政年份:2020
- 资助金额:
$ 23.28万 - 项目类别:
Quantitative MicroSPECT Imaging of Myocardial Blood Flow in Mice
小鼠心肌血流的定量 MicroSPECT 成像
- 批准号:
10663931 - 财政年份:2020
- 资助金额:
$ 23.28万 - 项目类别:
Quantitative MicroSPECT Imaging of Myocardial Blood Flow in Mice
小鼠心肌血流的定量 MicroSPECT 成像
- 批准号:
10442470 - 财政年份:2020
- 资助金额:
$ 23.28万 - 项目类别:
Expert System for Personalized Reconstruction of PET Acquisitions
PET 采集个性化重建专家系统
- 批准号:
9182252 - 财政年份:2016
- 资助金额:
$ 23.28万 - 项目类别:
Expert System for Personalized Reconstruction of PET Acquisitions
PET 采集个性化重建专家系统
- 批准号:
9292307 - 财政年份:2016
- 资助金额:
$ 23.28万 - 项目类别:
Super-Resolution PET Using Stepping of a Deliberately Misaligned Bed
使用故意错位床的步进进行超分辨率 PET
- 批准号:
8569816 - 财政年份:2013
- 资助金额:
$ 23.28万 - 项目类别:
Preclinical cardiac imaging package for clinical SPECT systems
用于临床 SPECT 系统的临床前心脏成像包
- 批准号:
8716561 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
Preclinical cardiac imaging package for clinical SPECT systems
用于临床 SPECT 系统的临床前心脏成像包
- 批准号:
8889715 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
Preclinical cardiac imaging package for clinical SPECT systems
用于临床 SPECT 系统的临床前心脏成像包
- 批准号:
8516091 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
Preclinical cardiac imaging package for clinical SPECT systems
用于临床 SPECT 系统的临床前心脏成像包
- 批准号:
8372831 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
相似海外基金
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
- 批准号:
RGPIN-2015-05926 - 财政年份:2019
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Grants Program - Individual
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
- 批准号:
RGPIN-2015-05926 - 财政年份:2018
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Grants Program - Individual
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
- 批准号:
RGPIN-2015-05926 - 财政年份:2017
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Grants Program - Individual
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
- 批准号:
RGPIN-2015-05926 - 财政年份:2016
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Grants Program - Individual
Event detection algorithms in decision support for animals health surveillance
动物健康监测决策支持中的事件检测算法
- 批准号:
385453-2009 - 财政年份:2015
- 资助金额:
$ 23.28万 - 项目类别:
Collaborative Research and Development Grants
Algorithms to generate designs of potency experiments that use far fewer animals
生成使用更少动物的效力实验设计的算法
- 批准号:
8810865 - 财政年份:2015
- 资助金额:
$ 23.28万 - 项目类别:
Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals
小动物时域漫射光学断层成像重建算法
- 批准号:
RGPIN-2015-05926 - 财政年份:2015
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Grants Program - Individual
Event detection algorithms in decision support for animals health surveillance
动物健康监测决策支持中的事件检测算法
- 批准号:
385453-2009 - 财政年份:2013
- 资助金额:
$ 23.28万 - 项目类别:
Collaborative Research and Development Grants
Development of population-level algorithms for modelling genomic variation and its impact on cellular function in animals and plants
开发群体水平算法来建模基因组变异及其对动植物细胞功能的影响
- 批准号:
FT110100972 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
ARC Future Fellowships
Advanced computational algorithms for brain imaging studies of freely moving animals
用于自由活动动物脑成像研究的先进计算算法
- 批准号:
DP120103813 - 财政年份:2012
- 资助金额:
$ 23.28万 - 项目类别:
Discovery Projects