基于迭代和深度学习重建CT图像的噪声功率谱和调制传递函数比较:初步经验研究

IF 0.7 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Polish Journal of Medical Physics and Engineering Pub Date : 2023-06-01 DOI:10.2478/pjmpe-2023-0012
Adiwasono M. B. Setiawan, C. Anam, E. Hidayanto, H. Sutanto, A. Naufal, G. Dougherty
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引用次数: 1

摘要

深度学习图像重建(DLIR)是一种非常新的图像重建方法,已经可用于商业用途。我们评估了DLIR图像的质量,并将其与最新的自适应统计迭代重建(ASIR-V)算法在噪声功率谱(NPS)和调制传递函数(MTF)方面的图像质量进行了比较。方法采用512多层计算机断层扫描(CT)扫描Revolution QA假体(GE Healthcare, USA)和20 cm水假体(GE Healthcare, USA)。在50mm视场(FOV)下重建了Revolution QA模体内的钨丝图像。采用不同ASIR-V强度(即0、10、20、30、40、50、60、70、80、90、100%)和dlir(即低、中、高)重建图像,评估MTF。重建20 cm水影的图像,以评估NPS。结果DLIR和ASiR-V两种重建算法的MTF相似。DLIR低的峰值频率(fp)与ASIR-V在50,60,70%处相当;DLIR培养基与ASIR-V相当,为80%;DLIR高可与ASIR-V媲美,为100%。DLIR低的平均频率(fA)与ASIR-V相当,为40%;DLIR培养基在50%时与ASIR-V相当;DLIR最高为70%,与ASIR-V相当。DLIR和ASIR-V都能够降低噪声,但它们的质地不同。结论DLIR图像的噪声在高低频较均匀,而ASIR-V图像的噪声在高频较集中。两种重建算法的MTF相似。DLIR方法的降噪效果优于ASIR-V重建。
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Comparison of noise-power spectrum and modulation-transfer function for CT images reconstructed with iterative and deep learning image reconstructions: An initial experience study
Abstract Introduction Deep learning image reconstruction (DLIR) is a very recent image reconstruction method that is already available for commercial use. We evaluated the quality of DLIR images and compared it to the quality of images from the latest adaptive statistical iterative reconstruction (ASIR-V) algorithm in terms of noise-power spectrum (NPS) and modulation-transfer function (MTF). Methods We scanned a Revolution QA phantom (GE Healthcare, USA) and a 20 cm water phantom (GE Healthcare, USA) with our 512 multi-slice computed tomography (CT) scanner. Images of the tungsten wire within the Revolution QA phantom were reconstructed with a 50 mm field of view (FOV). The images were reconstructed with various ASIR-V strengths (i.e. 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100%) and DLIRs (i.e. low, medium, and high) to assess the MTF. The images from the 20 cm water phantom were reconstructed with the same configuration to assess the NPS. Results The MTF was similar for both reconstruction algorithms of DLIR and ASiR-V. The peak frequency (fp) of the DLIR low was comparable to that from ASIR-V at 50, 60, 70%; the DLIR medium was comparable to ASIR-V at 80%; and the DLIR high was comparable to ASIR-V at 100%. The average frequency (fA) of the DLIR low was comparable to that from ASIR-V at 40%; the DLIR medium was comparable to ASIR-V at 50%; and the DLIR high was comparable to ASIR-V at 70%. Both the DLIR and ASIR-V were able to reduce noise, but they had a different texture. Conclusions The noise in the DLIR images was more homogenous at high and low frequencies, while in the ASIR-V images, the noise was more concentrated at high frequencies. The MTF was similar for both reconstruction algorithms. The DLIR method showed a better noise reduction than the ASIR-V reconstruction.
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来源期刊
Polish Journal of Medical Physics and Engineering
Polish Journal of Medical Physics and Engineering RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
1.30
自引率
0.00%
发文量
19
期刊介绍: Polish Journal of Medical Physics and Engineering (PJMPE) (Online ISSN: 1898-0309; Print ISSN: 1425-4689) is an official publication of the Polish Society of Medical Physics. It is a peer-reviewed, open access scientific journal with no publication fees. The issues are published quarterly online. The Journal publishes original contribution in medical physics and biomedical engineering.
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