Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography
Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography
批准号:
8593192
负责人:
Lei Xing
金额:
$54.08万
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
项目状态:
已结题
起止时间:
2013-08-01 至 2017-07-31
关键词:
AccountingAdverse effectsAlgorithmsAnatomyBrachytherapy SeedsBreathingCharacteristicsChildhoodClinicalCohort StudiesCoupledDataDentalDiagnostic radiologic examinationDoseExcisionFoundationsFutureGoalsHealthHip region structureImageImaging TechniquesIndividualKnowledgeLiverLocationLungMalignant NeoplasmsMalignant neoplasm of brainMathematicsMeasurementMedicalMetalsMethodsMorphologic artifactsMotionNoisePancreasPathologyPatientsPhasePhysicsProceduresProcessProsthesisRadiationRadiation OncologyRadiation therapyRelative (related person)ResearchResearch DesignResearch PersonnelRespirationRetinal ConeRiskScanningSchemeSecond Primary CancersShapesShoulderSolutionsSystemTechniquesTechnologyTestingTimeTissuesUncertaintyUnited States National Institutes of HealthWeightbasecancer imagingclinical applicationclinical decision-makingclinical practicecomputerized data processingcomputerized toolscone-beam computed tomographydesignexperienceimage guided interventionimage guided radiation therapyimage processingimage reconstructionimprovedinnovationinterestleukemialifetime risknext generationpatient populationprocess optimizationpublic health relevancereconstructionresearch clinical testingresponsescientific computingspatiotemporaltooltreatment planningtumor
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Cone beam CT (CBCT) imaging is becoming an indispensable tool in image guided interventions and many other clinical applications. The data processing method in current CBCT imaging is, however, deficient in multiple aspects, which often leads to severe artifacts and results in high imaging dose to the patients. The poor image quality causes much uncertainty in clinical decision-making and seriously impedes the maximal utilization of the technology. This project is directed at developing CBCT into a clinically accurate and reliable technique for delineation of tumor target, interventional guidance and radiation therapy treatment planning. In response to NIH PAR-09-218, we have assembled a team of investigators comprised of leaders in the fields of radiation oncology, medical physics, image and signal processing, optimization and applied mathematics and established research themes and projects that unify the common interests and expertise of these investigators. We draw on our extensive experience in CBCT imaging and scientific computing to develop the next generation of artifact-free and ultra-low dose CBCT. A number of innovative strategies to dealing with sparse, noisy, and missing data in CBCT imaging will be established. Specific aims are: (1) To achieve ultra-low dose CBCT by utilization of patient-specific prior data and compressed sensing; (2) to develop a divide-and-conquer approach for metal artifact removal in CBCT reconstruction; and (3) to obtain motion artifact-free images by effective use of inter-phase correlation of the projections. Successful completion of this project will provide high quality CBCT images with orders of magnitude less imaging dose. For image guided radiation therapy, the improved image quality will make accurate CBCT-based dose calculation and replanning possible, which will lay the foundation for next generation of adaptive therapy to optimally compensate for the patient setup error and inter- fractional anatomy change. With the reduction in imaging dose, the proposed technique will significantly reduce the risk of radiation-induced secondary cancers and contribute to the safe and efficient use of volumetric X-ray imaging techniques in routine clinical practice.
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海外基金