Noise Reduction in Brain CT: A Comparative Study of Deep Learning and Hybrid Iterative Reconstruction Using Multiple Parameters.

IF 2.2 4区医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Tomography Pub Date : 2024-12-18 DOI:10.3390/tomography10120147

Yusuke Inoue, Hiroyasu Itoh, Hirofumi Hata, Hiroki Miyatake, Kohei Mitsui, Shunichi Uehara, Chisaki Masuda

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Abstract

Objectives: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT).

Methods: CT images of a 16 cm dosimetry phantom, a head phantom, and the brains of 11 patients were reconstructed using filtered backprojection (FBP) and various levels of DLR and HIR. The slice thickness was 5, 2.5, 1.25, and 0.625 mm. Phantom imaging was also conducted at various tube currents. The noise reduction ratio was calculated using FBP as the reference. For patient imaging, overall image quality was visually compared between DLR and HIR images that exhibited similar noise reduction ratios.

Results: The noise reduction ratio increased with increasing levels of DLR and HIR in phantom and patient imaging. For DLR, noise reduction was more pronounced with decreasing slice thickness, while such thickness dependence was less evident for HIR. Although the noise reduction effects of DLR were similar between the head phantom and patients, they differed for the dosimetry phantom. Variations between imaging objects were small for HIR. The noise reduction ratio was low at low tube currents for the dosimetry phantom using DLR; otherwise, the influence of the tube current was small. In terms of visual image quality, DLR outperformed HIR in 1.25 mm thick images but not in thicker images.

Conclusions: The degree of noise reduction using DLR depends on the slice thickness, tube current, and imaging object in addition to the level of DLR, which should be considered in the clinical use of DLR. DLR may be particularly beneficial for thin-slice imaging.

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脑CT降噪：深度学习与多参数混合迭代重建的比较研究。

目的：评估深度学习重建（DLR）和混合迭代重建（HIR）在脑计算机断层扫描（CT）中的降噪效果。方法：采用滤波后反投影（FBP）和不同水平DLR和HIR对11例患者的16 cm剂量学影、头部影和大脑进行重建。切片厚度分别为5、2.5、1.25、0.625 mm。幻影成像也在不同的管电流下进行。以FBP为基准计算降噪比。对于患者成像，视觉上比较具有相似降噪比的DLR和HIR图像的整体图像质量。结果：幻影和患者影像中DLR和HIR水平的增加，降噪比增加。对于DLR，随着切片厚度的减小，降噪更加明显，而对于HIR，这种厚度依赖性不太明显。虽然DLR的降噪效果在头部幻像和患者之间相似，但在剂量学幻像中存在差异。HIR成像对象之间的差异很小。在低管电流条件下，DLR剂量测量模体的降噪比较低；否则，管电流的影响很小。在视觉图像质量方面，DLR在1.25 mm厚的图像中优于HIR，但在较厚的图像中优于HIR。结论：DLR的降噪程度除与DLR水平有关外，还与层厚、管电流、成像对象等因素有关，在临床应用DLR时应予以考虑。DLR可能特别有利于薄层成像。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Tomography Medicine-Radiology, Nuclear Medicine and Imaging

CiteScore

2.70

自引率

10.50%

发文量

222

期刊介绍： TomographyTM publishes basic (technical and pre-clinical) and clinical scientific articles which involve the advancement of imaging technologies. Tomography encompasses studies that use single or multiple imaging modalities including for example CT, US, PET, SPECT, MR and hyperpolarization technologies, as well as optical modalities (i.e. bioluminescence, photoacoustic, endomicroscopy, fiber optic imaging and optical computed tomography) in basic sciences, engineering, preclinical and clinical medicine. Tomography also welcomes studies involving exploration and refinement of contrast mechanisms and image-derived metrics within and across modalities toward the development of novel imaging probes for image-based feedback and intervention. The use of imaging in biology and medicine provides unparalleled opportunities to noninvasively interrogate tissues to obtain real-time dynamic and quantitative information required for diagnosis and response to interventions and to follow evolving pathological conditions. As multi-modal studies and the complexities of imaging technologies themselves are ever increasing to provide advanced information to scientists and clinicians. Tomography provides a unique publication venue allowing investigators the opportunity to more precisely communicate integrated findings related to the diverse and heterogeneous features associated with underlying anatomical, physiological, functional, metabolic and molecular genetic activities of normal and diseased tissue. Thus Tomography publishes peer-reviewed articles which involve the broad use of imaging of any tissue and disease type including both preclinical and clinical investigations. In addition, hardware/software along with chemical and molecular probe advances are welcome as they are deemed to significantly contribute towards the long-term goal of improving the overall impact of imaging on scientific and clinical discovery.