论文标题
使用先验辅助深度学习对MR图像进行回顾性运动校正
Retrospective Motion Correction of MR Images using Prior-Assisted Deep Learning
论文作者
论文摘要
在MRI中，运动伪像是最常见的人工制品类型之一。它们可以降低图像并使它们无法使用以进行准确的诊断。已经提出了传统方法，例如前瞻性或回顾性运动校正，以避免或减轻运动伪像。最近，已经提出了基于深度学习方法的其他几种方法来解决此问题。这项工作建议通过包含作为图像先验的其他信息来增强现有深度学习模型的性能。所提出的方法显示出令人鼓舞的结果，并将进一步研究临床有效性。
In MRI, motion artefacts are among the most common types of artefacts. They can degrade images and render them unusable for accurate diagnosis. Traditional methods, such as prospective or retrospective motion correction, have been proposed to avoid or alleviate motion artefacts. Recently, several other methods based on deep learning approaches have been proposed to solve this problem. This work proposes to enhance the performance of existing deep learning models by the inclusion of additional information present as image priors. The proposed approach has shown promising results and will be further investigated for clinical validity.
