Active Sampling for Accelerated MRI with Low-Rank Tensors.
Active Sampling for Accelerated MRI with Low-Rank Tensors.
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使用低秩张量加速MRI的主动采样。
DOI：
10.1109/embc48229.2022.9871360
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发表时间：
2022-07
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磁共振成像（MRI）是一种强大的成像方式，它给医学和生物学带来了革命性的变化。高维MRI的成像速度往往有限，这限制了它的实际应用。最近，低秩张量模型已被用于实现稀疏采样的快速磁共振成像。大多数现有方法使用一些预先定义的采样设计，而针对低秩张量成像的主动感知尚未得到探索。在本文中，我们引入了一种用于快速磁共振成像的主动低秩张量模型。我们提出了一种基于委员会查询模型的主动采样方法，利用了低秩张量结构的优势。在一个三维MRI数据集上进行的数值实验证明了所提方法的有效性。
Magnetic resonance imaging (MRI) is a powerful imaging modality that revolutionizes medicine and biology. The imaging speed of high-dimensional MRI is often limited, which constrains its practical utility. Recently, low-rank tensor models have been exploited to enable fast MR imaging with sparse sampling. Most existing methods use some pre-defined sampling design, and active sensing has not been explored for low-rank tensor imaging. In this paper, we introduce an active low-rank tensor model for fast MR imaging. We propose an active sampling method based on a Query-by-Committee model, making use of the benefits of low-rank tensor structure. Numerical experiments on a 3-D MRI data set demonstrate the effectiveness of the proposed method.