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SU-F-303-03: Auto-Alignment of 2D Cine Imaging Planes for Real-Time Motion Management During MRI-GRT

E.S. Paulson-2015-06-01-Medical Physics
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TL;DRAbstract

Purpose: Spatial-temporal-contrast resolution tradeoffs preclude acquisition of real-time 3D MRI volumes for exception gating and target tracking. Consequently, acquisition of 2D imaging planes has been proposed. However, to minimize through-plane motion the orientation of the 2D imaging planes must be chosen appropriately. The goal of this work was to develop a methodology to auto-align 2D cine imaging planes for real-time cine imaging on MRI-gRT systems. Methods: Phase-resolved 4D MR images of a healthy volunteer set up in treatment position were acquired at 3T. Following offline reconstruction in MATLAB, the binned 4D MR images were transferred to MIM (MIM Software, Cleveland, OH). To simulate target, a contour of the right kidney was generated on the 0% phase image and then deformably propagated to the remaining nine respiratory phase images. Dynamic, 3D centroid motion of the kidney target was calculated at each respiratory phase. Principal component analysis was used to determine

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Purpose: Spatial-temporal-contrast resolution tradeoffs preclude acquisition of real-time 3D MRI volumes for exception gating and target tracking. Consequently, acquisition of 2D imaging planes has been proposed. However, to minimize through-plane motion the orientation of the 2D imaging planes must be chosen appropriately. The goal of this work was to develop a methodology to auto-align 2D cine imaging planes for real-time cine imaging on MRI-gRT systems. Methods: Phase-resolved 4D MR images of a healthy volunteer set up in treatment position were acquired at 3T. Following offline reconstruction in MATLAB, the binned 4D MR images were transferred to MIM (MIM Software, Cleveland, OH). To simulate target, a contour of the right kidney was generated on the 0% phase image and then deformably propagated to the remaining nine respiratory phase images. Dynamic, 3D centroid motion of the kidney target was calculated at each respiratory phase. Principal component analysis was used to determine

Keywords

Computer visionArtificial intelligenceCentroidComputer scienceMatch movingScannerNuclear medicineMedical imaging

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