Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati
Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati
批准号:
8513269
负责人:
Patrick Jean La Riviere
金额:
$24.62万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-24 至 2015-07-31
关键词:
AccelerationAccountingAffectAlgorithmsBiological ModelsBlood VesselsChronic Kidney FailureClinicalClinical ResearchContrast MediaDataDatabasesDetectionDiagnosticDiscriminationDoseDrug usageEmergency SituationEnteralEvaluationFiltrationFistulaGoalsHematomaHypersensitivityImageImpaired Renal FunctionInformation SystemsIntestinesIntravenousKidney CalculiLeadLesionMeasurementMethodsModelingMorphologic artifactsNephrotoxicNoiseObesityPatientsPerforationPerformancePropertyRadiationRecipeResolutionRetroperitoneal SpaceScanningSecureSignal TransductionSliceSpecific qualifier valueStatistical ModelsStructureSystemTestingTimeTissuesTomography, Computed, ScannersTubeWorkX-Ray Computed Tomographyabstractingbasedensitydetectorflexibilityimage reconstructionimprovedinstrumentmathematical modelnovelphysical propertypreferenceradiation detectorradiologistreconstructionrestorationscreeningstatistics
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Abstract
Computed tomography (CT) scans are performed both with and without intravenous (IV) and/or enteric
contrast, drugs used to improve the discrimination of vascular structures, improve tissue characterization,
search for bowel perforation or fistulae, and many related applications. IV contrast is nephrotoxic, especially in
patients with impaired renal function. Consequently, many patients cannot or should not have IV contrast, so
non-contrast CT (NC-CT) scans are often performed, despite their intrinsic limitations, which include poor
contrast-to-noise properties. There is a critical and immediate need to improve the diagnostic performance of
such unenhanced scans.
The long-term goal of this project is to overcome the limitations of NC-CT using statistically principled image
reconstruction optimized for specific applications. The intrinsic contrast-to-noise will be increased by reducing
noise while preserving resolution using projection-domain smoothing and restoration with explicit models of
measurement statistics. Successful completion of this work may provide superior CT imaging performance for
patients with chronic kidney disease, contrast allergy, obesity, and for screening applications where radiation
dose is limited.
There are 4 specific aims:
(1) An instrument-specific mathematical model will be synthesized using the statistical and physical properties
of a particular clinical CT scanner.
(2) Penalized-likehood sinogram restoration methods will be implemented on NC-CT exams.
(3) The NC-CT image reconstruction strategy will be implemented on dedicated hardware to achieve clinically
useful reconstruction times.
(4) The penalized-likelihood sinogram restoration strategy will be optimized to deliver tailored algorithms for
specific NC-CT applications and tested on a database of clinical cases.
On completion, this project will provide a validated means to reconstruct non-contrast CT scans with
significantly improved signal-to-noise and contrast-to-noise, thereby improving the diagnostic performance for
emergency examinations. The system will be flexible and clinically feasible for multicenter testing in selected
applications. The reconstruction methods will be optimized for the most promising applications, and preliminary
measurements of diagnostic performance will be available. Project Narrative
The long term goal of this project is to develop and apply statistically principled image reconstruction
approaches for non-contrast computed tomography (CT). The intrinsic contrast-to-noise will be increased by
reducing noise while preserving resolution using projection-domain smoothing and restoration with explicit
models of measurement statistics.
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Variable temporal sampling and tube current modulation for myocardial blood flow estimation from dose-reduced dynamic computed tomography.
可变时间采样和管电流调制,用于从剂量减少的动态计算机断层扫描估计心肌血流。
DOI:
10.1117/1.jmi.4.2.026002
发表时间:
2017
期刊:
Journal of medical imaging (Bellingham, Wash.)
影响因子:
--
作者:
[Modgil,Dimple, Bindschadler,MichaelD, Alessio,AdamM, LaRivière,PatrickJ]
通讯作者:
LaRivière,PatrickJ
DOI:
10.1088/0031-9155/59/7/1533
发表时间:
2014-04-07
期刊:
Physics in medicine and biology
影响因子:
3.5
作者:
[Bindschadler M, Modgil D, Branch KR, La Riviere PJ, Alessio AM]
通讯作者:
Alessio AM
DOI:
10.1088/0031-9155/60/20/8025
发表时间:
2015-10-21
期刊:
Physics in medicine and biology
影响因子:
3.5
作者:
[Modgil D, Rigie DS, Wang Y, Xiao X, Vargas PA, La Rivière PJ]
通讯作者:
La Rivière PJ
DOI:
10.1109/tns.2011.2167632
发表时间:
2011-12
期刊:
IEEE transactions on nuclear science
影响因子:
1.8
作者:
[Meng LJ, Li N, La Riviere PJ]
通讯作者:
La Riviere PJ
DOI:
10.1118/1.3594547
发表时间:
2011-08
期刊:
Medical physics
影响因子:
3.8
作者:
[P. Vargas;P. L. La Riviere]
通讯作者:
P. Vargas;P. L. La Riviere
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Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati
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负责人:Patrick Jean La Riviere
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依托单位:
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Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati
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依托单位:
海外基金