欢迎来到《四川大学学报(医学版)》
徐旭, 彭婉琳, 张金戈, 等. 基于人工智能的滤波和插值图像重建算法在腹部磁共振图像降噪中的价值[J]. 四川大学学报(医学版), 2021, 52(2): 293-299. DOI: 10.12182/20210360104
引用本文: 徐旭, 彭婉琳, 张金戈, 等. 基于人工智能的滤波和插值图像重建算法在腹部磁共振图像降噪中的价值[J]. 四川大学学报(医学版), 2021, 52(2): 293-299. DOI: 10.12182/20210360104
XU Xu, PENG Wan-lin, ZHANG Jin-ge, et al. The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising[J]. Journal of Sichuan University (Medical Sciences), 2021, 52(2): 293-299. DOI: 10.12182/20210360104
Citation: XU Xu, PENG Wan-lin, ZHANG Jin-ge, et al. The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising[J]. Journal of Sichuan University (Medical Sciences), 2021, 52(2): 293-299. DOI: 10.12182/20210360104

基于人工智能的滤波和插值图像重建算法在腹部磁共振图像降噪中的价值

The Application Value of Artificial Intelligence-based Filtering and Interpolated Image Reconstruction Algorithm in Abdominal Magnetic Resonance Image Denoising

  • 摘要:
      目的  比较腹部磁共振序列中常规滤波技术和基于人工智能的滤波和插值(artificial intelligence based filtering and interpolation,AIFI)的重建技术的降噪性能,并探讨AIFI在图像降噪时的最优参数。
      方法  回顾性纳入我院60例进行上腹部磁共振检查的患者,将其T1加权成像(T1-weighted image,T1WI)、T2加权成像(T2-weighted image,T2WI)和双回波序列的原始图像分别进行常规滤波和不同强度的AIFI技术重建,比较重建图像的客观图像质量指标——图像峰值信噪比(peak signal noise ratio,pSNR)和图像锐利度。两名医生对重建图像噪声、对比度、清晰度、总体图像质量进行评分,比较其评分结果并计算观察者间一致性。
      结果  相较于原始图像,三序列(T1WI、T2WI和双回波序列)图像经降噪技术重建后图像的pSNR、图像锐利度均有不同程度的提高(P均<0.05),且在T1WI中使用常规滤波和AIFI组合重建时,T2WI和echo1序列中AIFI level≥3及组合重建时,echo2序列中AIFI level≥4及组合重建时的图像客观质量评分高于常规滤波(P均<0.05)。对三序列主观评分中常规滤波重建、AIFI重建(除AIFI level=1)、组合重建图像各序列中的图像噪声、对比度、清晰度、整体图像质量的评分均高于原始图像(P均<0.05),AIFI level=5时,图像对比度得分均有所降低(P<0.05)。两医生评分具有良好的一致性(r均>0.75,P<0.05)。经多维度比较,腹部MRI使用AIFI技术进行降噪时的最优参数T1WI为常规滤波+AIFI level=3;T2WI和双回波序列中为AIFI level=4。
      结论  AIFI技术在中高level的降噪表现优于常规滤波,是一种具有良好应用前景的降噪技术,其在腹部MRI的最优参数T1WI为常规滤波+AIFI level=3;T2WI和双回波序列中为AIFI level=4。

     

    Abstract:
      Objective  To compare the noise reduction performance of conventional filtering and artificial intelligence-based filtering and interpolation (AIFI) and to explore for optimal parameters of applying AIFI in the noise reduction of abdominal magnetic resonance imaging (MRI).
      Methods  Sixty patients who underwent upper abdominal MRI examination in our hospital were retrospectively included. The raw data of T1-weighted image (T1WI), T2-weighted image (T2WI), and dualecho sequences were reconstructed with two image denoising techniques, conventional filtering and AIFI of different levels of intensity. The difference in objective image quality indicators, peak signal-to-noise ratio (pSNR) and image sharpness, of the different denoising techniques was compared. Two radiologists evaluated the image noise, contrast, sharpness, and overall image quality. Their scores were compared and the interobserver agreement was calculated.
      Results  Compared with the original images, improvement of varying degrees were shown in the pSNR and the sharpness of the images of the three sequences, T1W1, T2W2, and dual echo sequence, after denoising filtering and AIFI were used (all P<0.05). In addition, compared with conventional filtering, the objective quality scores of the reconstructed images were improved when conventional filtering was combined with AIFI reconstruction methods in T1WI sequence, AIFI level≥3 was used in T2WI and echo1 sequence, and AIFI level≥4 was used in echo2 sequence (all P<0.05). The subjective scores given by the two radiologists for the image noise, contrast, sharpness, and overall image quality in each sequence of conventional filtering reconstruction, AIFI reconstruction (except for AIFI level=1), and two-method combination reconstruction were higher than those of the original images (all P<0.05). However, the image contrast scores were reduced for AIFI level=5. There was good interobserver agreement between the two radiologists (all r>0.75, P<0.05). After multidimensional comparison, the optimal parameters of using AIFI technique for noise reduction in abdominal MRI were conventional filtering+AIFI level=3 in the T1WI sequence and AIFI level=4 in the T2WI and dualecho sequences.
      Conclusion  AIFI is superior to filtering in imaging denoising at medium and high levels. It is a promising noise reduction technique. The optimal parameters of using AIFI for abdominal MRI are Filtering+AIFI level=3 in the T1WI sequence and AIFI level=4 in T2WI and dualecho sequences.

     

/

返回文章
返回