【摘要】：加快掃描速度是磁共振成像(Magnetic Resonance Imaging,MRI)發(fā)展中重要的一步,并行成像(ParallelImaging,PI)利用相陣列線圈的空間信息和特定的重建算法,能有效縮短掃描時間。其中在臨床醫(yī)療中應(yīng)用最廣的是SENSE(Sensitivity Encoding for Fast MRI)和 GRAPPA(Generalized Auto-calibrating Partially Parallel Acquisition)。壓縮感知(CompressedSensing,CS)是從另一個角度進(jìn)行加速采樣的新技術(shù),該方法基于磁共振圖像的稀疏特性,對k空間進(jìn)行隨機欠采樣,并通過優(yōu)化重建算法去除非相干偽影,得到可以用于臨床診斷的磁共振圖像。由于并行成像和壓縮感知基礎(chǔ)理論的不同以及采樣方式上的不同,已有學(xué)者結(jié)合兩種算法來進(jìn)一步提高磁共振圖像的掃描速度,并通過特定算法來重建得到最終圖像。本文提出了一種新的結(jié)合并行成像和壓縮感知加速磁共振成像的方法。在重建過程中,采用分步重建的方式,用GRAPPA重建填充每個通道的部分k空間數(shù)據(jù),再用CS重建每個通道的全k空間數(shù)據(jù),最后再進(jìn)行通道合并得到最終重建圖像。其中在采樣方式上,本文設(shè)計了一種局部沿著相位編碼方向等間隔采樣模板,再利用該模板對全k空間進(jìn)行隨機采樣,該方法可以有效的利用GRAPPA盡可能重建更多的k空間數(shù)據(jù)。同時本文也討論了 GRAPPA的重建數(shù)據(jù)與后續(xù)CS重建中保真權(quán)重的關(guān)系,進(jìn)而優(yōu)化了 CS中的目標(biāo)函數(shù),借助GRAPPA重建數(shù)據(jù)來提高CS重建圖像的質(zhì)量。本文通過大量不同模態(tài)的磁共振圖像后處理模擬實驗,證明了本文提出的方法可以在相同采樣率的情況下,獲得較好的重建結(jié)果。
[Abstract]:Accelerating scanning speed is an important step in the development of magnetic resonance imaging (Magnetic Resonance Imaging,MRI). Parallel imaging (ParallelImaging,PI) can effectively shorten the scanning time by using the spatial information of phase array coil and special reconstruction algorithm. SENSE (Sensitivity Encoding for Fast MRI) and GRAPPA (Generalized Auto-calibrating Partially Parallel Acquisition). Are the most widely used in clinical medicine. Compression sensing (CompressedSensing,CS) is a new technique for accelerating sampling from another point of view. Based on the sparse characteristic of magnetic resonance images, this method performs random under-sampling in k-space, and uses an optimized reconstruction algorithm to remove coherent artifacts. Magnetic resonance imaging can be used for clinical diagnosis. Due to the difference of the basic theory of parallel imaging and compression sensing and the difference of sampling methods, some scholars have combined two algorithms to further improve the scanning speed of magnetic resonance image and reconstruct the final image by a specific algorithm. In this paper, a new method combining parallel imaging with compression sensing accelerated magnetic resonance imaging is proposed. In the process of reconstruction, the partial k space data of each channel is reconstructed with GRAPPA, then the full k space data of each channel is reconstructed by CS, and the final reconstructed image is obtained by channel merging. In the sampling mode, this paper designs a local sampling template with equal interval along the direction of phase coding, and then uses the template to sample the whole k space randomly. This method can effectively use GRAPPA to reconstruct more k-space data as much as possible. At the same time, this paper also discusses the relationship between GRAPPA reconstruction data and fidelity weight in subsequent CS reconstruction, and then optimizes the objective function in CS, and improves the quality of CS reconstructed image by GRAPPA reconstruction data. In this paper, a large number of post-processing simulations of magnetic resonance images with different modes are carried out, and it is proved that the proposed method can obtain better reconstruction results under the same sampling rate.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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本文編號：2402725