Model-Based Reconstruction for High-Spatial Resolution Cone-Beam Computed Tomography
基于模型的高空间分辨率锥形束计算机断层扫描重建
基本信息
- 批准号:9259452
- 负责人:
- 金额:$ 4.4万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-03-01 至 2019-02-28
- 项目状态:已结题
- 来源:
- 关键词:AlgorithmsAttentionBiological ModelsBreast Cancer DetectionBreast MicrocalcificationClinicalClinical ResearchComputer SimulationComputer softwareDataDegenerative polyarthritisDentalDetectionDiagnosisDiagnostic radiologic examinationDoseElectronicsEnsureEquilibriumFutureGeometryGoalsGoldImageImage AnalysisInvestigationLeast-Squares AnalysisLightLimb structureMammographyMeasurementMeasuresMethodologyMethodsModalityModelingMorphologyMotionNatureNoiseOtolaryngologyPerformancePositron-Emission TomographyPropertyRadiationRadiation therapyResearchResolutionRoentgen RaysRotationSamplingScanningSeriesSourceSpottingsStatistical ModelsStructureSystemTestingVariantWorkanalytical methodbasebonebone imagingbone visualizationclinical applicationclinical efficacyclinical imagingclinically relevantcone-beam computed tomographydesigndetectorexperimental studyfallshigh resolution imagingimage reconstructionimprovedin vivo imagingmathematical modelmicroCTnovelnuclear imagingpoint of careportabilityreconstructionresponsesimulationsingle photon emission computed tomographysubstantia spongiosasuccesstomographytool
项目摘要
Project Summary
The main goal of this work is to improve image quality, particularly resolution, of flat-panel cone-beam CT
(fpCBCT) systems. This modality is promising for its high resolution, adaptability to different geometries, and
portability. In particular, fpCBCT is being investigated for use in bone-morphology quantification and microcal-
cification detection, which are important in the study of osteoarthritis and detection breast cancer, respectively.
These tasks require high resolution to visualize trabecular bone and microcalcifications, and while fpCBCT resolu-
tion is superior to that of multi-detector CT, it is often unable to resolve these structures with sufficient detail. This
work aims to improve resolution by modeling different system blur and noise properties, and incorporating these
models in a model-based iterative reconstruction (MBIR) algorithm. MBIR methods have been increasingly pop-
ular in tomography due to their ability to generate higher quality images than traditional analytical methods. This
is largely due to the fact that MBIR methods include a noise model, a feature lacking in analytical methods such
as filtered backprojection. A MBIR method with an accurate flat-panel-specific mathematical model will result in
higher spatial resolution reconstructions. The following sources of blur will be measured and modeled on multiple
fpCBCT test benches: the extended X-Ray focal spot, the detector scintillator, detector lag, and gantry motion.
Noise correlation resulting from these blurs or readout electronics will also be measured and modeled. Particular
attention will be paid to the shift-variant nature of these blurs which, along with noise correlation, has been tradi-
tionally overlooked in current CT and fpCBCT reconstruction methods. These models will balance accuracy with
computationally efficient so they may be used in iterative methods. Novel MBIR methods will be developed to in-
corporate a wide range of system models, including those developed in this work. These algorithms will be used to
reconstruct data acquired in simulation and on multiple fpCBCT test benches. The importance of each blur/noise
model will be evaluated with a range of system properties and acquisition settings. Data will be reconstructed
using the new, more accurate methods/models and traditional methods/models for comparison. Image quality
will be assessed using a variety of metrics, including resolution, spatial noise, segmentation quality, modulation
transfer functions, and noise power spectra. For example, the ability to segment trabecular bone will provide a
clinically relevant image quality metric. Thus, this work will result in novel MBIR methods, detailed models of blur
and noise correlation applicable to many fpCBCT systems, and a detailed analysis the image quality improve-
ments resulting from these methods. While this work will focus on high-resolution imaging of bone morphology,
it will improve the ability of fpCBCT to accomplish other high-resolution clinical tasks by improving resolution in
current systems. Additionally, this work will provide a software solution to hardware induced image quality limita-
tions, providing avenues not only to extend imaging performance in currently available system, but also to provide
improved trade-offs and a way to relax hardware constraints in the design of future fpCBCT systems.
项目总结
项目成果
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