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Optimization transfer approach to joint registration / reconstruction for motion-compensated image reconstruction

机译:用于运动补偿图像重建的联合配准/重建的优化传递方法

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Motion artifacts in image reconstruction problems can be reduced by performing image motion estimation and image reconstruction jointly using a penalized-likelihood cost function. However, updating the motion parameters by conventional gradient-based iterations can be computationally demanding due to the system model required in inverse problems. This paper describes an optimization transfer approach that leads to minimization steps for the motion parameters that have comparable complexity to those needed in image registration problems. This approach can simplify the implementation of motion-compensated image reconstruction (MCIR) methods when the motion parameters are estimated jointly with the reconstructed image.
机译:图像重建问题中的运动伪像可以通过使用惩罚似然成本函数联合执行图像运动估计和图像重建来减少。然而,由于反问题中需要的系统模型,通过常规的基于梯度的迭代来更新运动参数可能在计算上是需要的。本文介绍了一种优化传递方法,该方法可导致运动参数的最小化步骤,这些步骤的复杂度与图像配准问题所需的复杂度相当。当运动参数与重建图像一起被估计时,该方法可以简化运动补偿图像重建(MCIR)方法的实现。

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