Images are reconstructed from k-space data using a model-based image reconstruction that prospectively and simultaneously accounts for multiple non-idealities in accelerated single-shot-EPI acquisitions. In some implementations, nonlinear regularization (e.g., sparsity regularization) is also incorporated to mitigate noise amplification. The reconstructed images have reduced distortions and noise amplification effects relative to those images that are processed using conventional post-reconstruction techniques to correct for non-idealities.
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机译：使用基于模型的图像重建从 k 空间数据重建图像，该图像重建前瞻性地同时考虑了加速单次 EPI 采集中的多个非理想情况。在某些实现中，还结合了非线性正则化（例如，稀疏性正则化）来减轻噪声放大。与使用传统重建后技术处理的图像相比，重建的图像减少了失真和噪声放大效应，以校正非理想性。
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