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一种改良的 Tseng 算法在胸科疾病 CT 图像重建中的应用。

A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images.

机构信息

Department of Medical Diagnostic Imaging, College of Health Science, University of Sharjah, Sharjah, UAE.

Research Institute for Medical and Health Sciences, University of Sharjah, Sharjah, UAE.

出版信息

PLoS One. 2024 Jul 24;19(7):e0305728. doi: 10.1371/journal.pone.0305728. eCollection 2024.

Abstract

It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery.

摘要

众所周知,曾氏算法及其变体已成功应用于逼近单调算子和的零点。在这项研究中,我们使用改进的曾氏算法恢复了经过已知模糊函数和加性噪声退化的各种胸部疾病的计算机断层扫描(CT)图像。研究中使用的测试图像描绘了主动脉钙化、皮下气肿、主动脉扭曲、纵隔气肿和气腹。此外,我们还使用了著名的图像恢复工具来提高图像质量,并将恢复图像的质量与原始图像进行了比较。最后,该研究展示了在单调包含问题求解方面取得进展的潜力,特别是在医学图像恢复领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78f9/11268622/e2d8bdf68a49/pone.0305728.g001.jpg

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