Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part III
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part III
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医学图像计算和计算机辅助干预 - MICCAI 2016 - 第 19 届国际会议，希腊雅典，2016 年 10 月 17-21 日，会议记录，第三部分
DOI：
10.1007/978-3-319-46726-9_57
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Chen X
中科院分区：
文献类型：
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作者：
Chen X
我们提出了一种新的框架，用于根据多层MRI采集的流形对齐进行回溯性动态3D体积重建。K空间数据是在自由呼吸下以逐片方式使用径向黄金角轨迹连续采集的。在短时间窗口内获取的非重叠的连续简档被分组在一起。然后，使用流形对齐将来自所有切片的所有分组的轮廓同时嵌入到公共流形空间(MS)中，在该空间中，在相似呼吸状态下获得的轮廓彼此接近。随后，通过组合在MS中接近的轮廓，可以在每个分组的轮廓MS位置处重建3D体积。这使得原始多切片数据集能够用于基于在MS中建立的呼吸状态对应来重建动态3D序列。我们的方法在合成数据集和活体数据集上进行了评估。对于合成数据集，重建的动态序列与地面真实数据相比，归一化互相关达到0.98，峰值信噪比为26.64分贝。对于活体数据集，基于清晰度测量和视觉比较，我们的方法比使用自适应的中心k空间门控方法进行重建的效果更好。
We present a novel framework for retrospective dynamic 3D volume reconstruction from a multi-slice MRI acquisition using manifold alignment. K-space data are continuously acquired under free breathing using a radial golden-angle trajectory in a slice-by-slice manner. Non-overlapping consecutive profiles that were acquired within a short time window are grouped together. All grouped profiles from all slices are then simultaneously embedded using manifold alignment into a common manifold space (MS), in which profiles that were acquired at similar respiratory states are close together. Subsequently, a 3D volume can be reconstructed at each of the grouped profile MS positions by combining profiles that are close in the MS. This enables the original multi-slice dataset to be used to reconstruct a dynamic 3D sequence based on the respiratory state correspondences established in the MS. Our method was evaluated on both synthetic andin vivodatasets. For the synthetic datasets, the reconstructed dynamic sequence achieved a normalised cross correlation of 0.98 and peak signal to noise ratio of 26.64 dB compared with the ground truth. For thein vivodatasets, based on sharpness measurements and visual comparison, our method performed better than reconstruction using an adapted central k-space gating method.