Department of Radiology, Stanford University, Stanford, California, USA; Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, USA.
Magn Reson Med. 2013 Nov;70(5):1306-18. doi: 10.1002/mrm.24592. Epub 2012 Dec 27.
To present and validate a new method that formalizes a direct link between k-space and wavelet domains to apply separate undersampling and reconstruction for high- and low-spatial-frequency k-space data.
High- and low-spatial-frequency regions are defined in k-space based on the separation of wavelet subbands, and the conventional compressed sensing problem is transformed into one of localized k-space estimation. To better exploit wavelet-domain sparsity, compressed sensing can be used for high-spatial-frequency regions, whereas parallel imaging can be used for low-spatial-frequency regions. Fourier undersampling is also customized to better accommodate each reconstruction method: random undersampling for compressed sensing and regular undersampling for parallel imaging.
Examples using the proposed method demonstrate successful reconstruction of both low-spatial-frequency content and fine structures in high-resolution three-dimensional breast imaging with a net acceleration of 11-12.
The proposed method improves the reconstruction accuracy of high-spatial-frequency signal content and avoids incoherent artifacts in low-spatial-frequency regions. This new formulation also reduces the reconstruction time due to the smaller problem size.
提出并验证一种新方法，该方法将 k 空间和小波域之间的直接联系形式化，以便对高空间频率和低空间频率 k 空间数据进行单独的欠采样和重建。
基于小波子带的分离，在 k 空间中定义了高空间频率和低空间频率区域，将传统的压缩感知问题转化为局部 k 空间估计问题。为了更好地利用小波域的稀疏性，可以使用压缩感知对高空间频率区域进行压缩感知，而对低空间频率区域则可以使用并行成像。傅里叶欠采样也经过了定制，以更好地适应每种重建方法：随机欠采样用于压缩感知，规则欠采样用于并行成像。
使用所提出的方法的示例成功地重建了具有净加速 11-12 的高分辨率三维乳房成像中的低空间频率内容和精细结构。
所提出的方法提高了高空间频率信号内容的重建精度，并避免了低空间频率区域中的不连贯伪影。由于问题规模较小，这种新的公式还减少了重建时间。
