北京生物醫(yī)學(xué)工程

動態(tài)磁共振成像中利用時空濾波的非笛卡爾稀疏數(shù)據(jù)重建新算法

One New Algorithm of Utilizing Spatio-Temporal Filtering for the Reconstruction of Non-Cartesian Sparse Data in Dynamic MRI

作者：梅穎潔周愛珍王聰莫紀(jì)江陳武凡馮衍秋

單位：南方醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院醫(yī)學(xué)信息所（廣州510515）

關(guān)鍵詞：動態(tài)磁共振圖像；非笛卡爾；稀疏；Hanning濾波；高頻增強(qiáng)

分類號：

出版年·卷·期（頁碼）：2011·30·4（344-349）

摘要：

通過非笛卡爾稀疏采樣，可以顯著縮短磁共振成像數(shù)據(jù)采集時間，在動態(tài)磁共振中具有良好的應(yīng)用前景。現(xiàn)有的動態(tài)圖像重建算法主要利用信號在時間域上的相關(guān)性完成圖像重建，對信號在空間域上的相關(guān)性探討不足。本文提出利用時空濾波的非笛卡爾稀疏數(shù)據(jù)重建新算法，同時考慮采集信號在時間域和空間域上的相關(guān)性。對動態(tài)的磁共振數(shù)據(jù)在時間域上采用改進(jìn)的Hanning濾波，以克服數(shù)據(jù)量的不足；在空間域上，引入高頻增強(qiáng)約束以突出圖像中的細(xì)節(jié)信息。仿真實(shí)驗結(jié)果顯示，該方法重建出時間分辨率良好、細(xì)節(jié)比較清晰的圖像，實(shí)現(xiàn)了稀疏采集的非笛卡爾數(shù)據(jù)在k空間的重建。

Sparsely non-Cartesian sampling indicates a promising future for dynamic magnetic resonance imaging (MRI) because it can shorten acquisition time remarkably. Current reconstruction algorithms for dynamic images mainly utilize signal correlations in temporal domain, which insufficiently use the signal correlations in spatial domain. We proposed a new algorithm for the reconstruction of non-Cartesian sparse data in dynamic MRI, which exploited signal correlations in time to circumvent data sparsity and employed high-frequency enhancement in k-space to emphasize edge sharpness. Simulated experiments showed that this proposed approach allowed k-space based reconstruction results with good temporal resolution and spatial resolution of non-Cartesian sparse data in dynamic MRI.

參考文獻(xiàn)：

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