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利用全变差正则化最小绝对值偏差求解器提高静态 BLADE 磁共振成像的图像质量。

Improved Image Quality for Static BLADE Magnetic Resonance Imaging Using the Total-Variation Regularized Least Absolute Deviation Solver.

机构信息

Department of Diagnostic Medical Imaging, Madou Sin-Lau Hospital, Tainan 721, Taiwan.

Department of Finance, Chung Yuan Christian University, Chung Li 320, Taiwan.

出版信息

Tomography. 2021 Oct 8;7(4):555-572. doi: 10.3390/tomography7040048.

DOI:10.3390/tomography7040048
PMID:34698286
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8544655/
Abstract

In order to improve the image quality of BLADE magnetic resonance imaging (MRI) using the index tensor solvers and to evaluate MRI image quality in a clinical setting, we implemented BLADE MRI reconstructions using two tensor solvers (the least-squares solver and the L1 total-variation regularized least absolute deviation (L1TV-LAD) solver) on a graphics processing unit (GPU). The BLADE raw data were prospectively acquired and presented in random order before being assessed by two independent radiologists. Evaluation scores were examined for consistency and then by repeated measures analysis of variance (ANOVA) to identify the superior algorithm. The simulation showed the structural similarity index (SSIM) of various tensor solvers ranged between 0.995 and 0.999. Inter-reader reliability was high (Intraclass correlation coefficient (ICC) = 0.845, 95% confidence interval: 0.817, 0.87). The image score of L1TV-LAD was significantly higher than that of vendor-provided image and the least-squares method. The image score of the least-squares method was significantly lower than that of the vendor-provided image. No significance was identified in L1TV-LAD with a regularization strength of λ= 0.4-1.0. The L1TV-LAD with a regularization strength of λ= 0.4-0.7 was found consistently better than least-squares and vendor-provided reconstruction in BLADE MRI with a SENSitivity Encoding (SENSE) factor of 2. This warrants further development of the integrated computing system with the scanner.

摘要

为了提高 BLADE 磁共振成像（MRI）的图像质量并评估临床环境中的 MRI 图像质量，我们在图形处理单元（GPU）上使用两种张量求解器（最小二乘法求解器和 L1 全变分正则化最小绝对偏差（L1TV-LAD）求解器）实现了 BLADE MRI 重建。前瞻性采集 BLADE 原始数据，并以随机顺序呈现，然后由两位独立的放射科医生进行评估。评估得分先进行一致性检查，然后进行重复测量方差分析（ANOVA），以确定优越的算法。模拟结果表明，各种张量求解器的结构相似性指数（SSIM）在 0.995 到 0.999 之间。读者间的可靠性很高（组内相关系数（ICC）=0.845，95%置信区间：0.817，0.87）。L1TV-LAD 的图像评分明显高于供应商提供的图像和最小二乘法。最小二乘法的图像评分明显低于供应商提供的图像。正则化强度为 λ=0.4-1.0 时，L1TV-LAD 无显著性差异。在 SENSE 因子为 2 时，正则化强度为 λ=0.4-0.7 的 L1TV-LAD 始终优于最小二乘法和供应商提供的重建，这表明需要进一步开发与扫描仪集成的计算系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/e87a7a7284f8/tomography-07-00048-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/2b27eadfd880/tomography-07-00048-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/3796b2076c01/tomography-07-00048-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/4a6a1de6ae11/tomography-07-00048-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/b7e94e8cce90/tomography-07-00048-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/1e112fe07353/tomography-07-00048-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/755672ae294c/tomography-07-00048-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/c1b9fa2d5742/tomography-07-00048-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/b4a5b0ecfb48/tomography-07-00048-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/e87a7a7284f8/tomography-07-00048-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/2b27eadfd880/tomography-07-00048-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/3796b2076c01/tomography-07-00048-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/4a6a1de6ae11/tomography-07-00048-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/b7e94e8cce90/tomography-07-00048-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/1e112fe07353/tomography-07-00048-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/755672ae294c/tomography-07-00048-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/c1b9fa2d5742/tomography-07-00048-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/b4a5b0ecfb48/tomography-07-00048-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2177/8544655/e87a7a7284f8/tomography-07-00048-g008.jpg

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