High performance computing for deformable image registration: towards a new paradigm in adaptive radiotherapy.

By S. Samant, J. Xia, Pinar Muyan-Ozcelik, John Douglas Owens. 2008

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GPU computing in medical physics: a review. (2011, unknown): “70–72 Each of the ﬁve steps of the algo-rithm (namely spatial gradient, displacement, smoothing, image deformation, and stopping criterion) are implemented by as many kernels.”
A survey of GPU-based medical image computing techniques. (2012, methodology): “Moreover, the accelerated Demon’s algorithm has been further implemented on GPU utilizing CUDA, and high quality and excellent performance were achieved (96).”
An unsupervised convolutional neural network-based algorithm for deformable image registration (2018, unknown): “If the original simulation CT and corresponding contours could be deformably mapped to the CBCT, the dose could be calculated much more reliably, without increasing clinical workload (Chao et al 2008, Samant et al 2008, Xie et al 2008).”