| 李金霞,李静静,肖丹,赵宏波,朱守平.基于Z轴相关性Zero-Shot Noise2Noise降低低剂量CT图像噪声[J].中国医学影像技术,2024,40(11):1764~1768 |
| 基于Z轴相关性Zero-Shot Noise2Noise降低低剂量CT图像噪声 |
| Reducing noise of low dose CT images with Zero-Shot Noise2Noise based on Z-axis correlation |
| 投稿时间：2024-06-27 修订日期：2024-09-05 |
| DOI：10.13929/j.issn.1003-3289.2024.11.027 |
| 中文关键词: 噪声 低剂量 体层摄影术,X线计算机 机器学习 |
| 英文关键词:noise low dose tomography, X-ray computed machine learning |
| 基金项目:陕西省"十四五"教育科学规划2023年度课题(SGH23Y2459)、西安医学院第五批校级重点学科(12202306)。 |
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| 中文摘要: |
| 目的 观察基于Z轴相关性Zero-Shot Noise2Noise (ZS-N2N)方法降低低剂量CT (LDCT)图像噪声的价值。方法 选取癌症成像档案CT数据集,包括正常剂量CT (NDCT)图像和LDCT图像,胸、腹部图像各3组。采用ZS-N2N方法基于Z轴相关性降低LDCT图像噪声,与Self2Self、单纯ZS-N2N及传统Block-matching and 3D filtering (BM3D)方法进行对比,观察各算法峰值信噪比(PSNR)、结构相似度(SSIM)及降噪耗时。结果 降噪后,Self2Self降噪图像噪声明显;BM3D降噪图像结构边缘较模糊,存在部分细节丢失;单纯ZS-N2N和基于Z轴相关性的ZS-N2N降噪图像留有更多细节,质量较好。以Self2Self降低LDCT图像噪声的PSNR和SSIM较差、耗时较长,其余3种方法的PSNR、SSIM和耗时均相近;其中,基于Z轴相关性ZS-N2N的PSNR略高于BM3D和单纯ZS-N2N,但耗时仍略长。结论 基于Z轴相关性ZS-N2N对降低LDCT图像噪声具有较高价值。 |
| 英文摘要: |
| Objective To observe the value of Zero-Shot Noise2Noise (ZS-N2N) based on Z-axis correlation for reducing noise of low dose CT (LDCT) images. Methods CT data of the cancer imaging archive were enrolled, including normal dose CT (NDCT) images and LDCT images, with 3 sets of chest and 3 sets of abdominal images. Noise on LDCT images were reduced with ZS-N2N method based on Z-axis correlation, and the peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and time-consuming of reducing noise were compared with those of Self2Self, simple ZS-N2N and traditional Block-matching and 3D filtering (BM3D). Results After reducing noise, noise on Self2Self denoised images remained significant, the structure edges on BM3D denoised images were blurry with some details lost, while simple ZS-N2N and ZS-N2N based on Z-axis correlation denoised images preserved more details and had better quality. PSNR and SSIM of Self2Self denoised images were poor and the time-consuming were longer. PSNR, SSIM and time-consuming of the other 3 methods were similar, among which PSNR of ZS-N2N based on Z-axis correlation were slightly higher than BM3D and simple ZS-N2N, but the time-consuming were also slightly longer. Conclusion ZS-N2N based on Z-axis correlation had high value for reducing noise of LDCT images. |
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