基于主权批判网络(SCN)的胸部x射线图像超分辨率

P. V. Yeswanth, Raavi Raviteja, S. Deivalakshmi
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引用次数: 0

摘要

结核病是影响全球人民的一种普遍而严重的疾病。结核病的成功诊断对于提高生存率和成功的治疗过程至关重要。由于医疗技术的进步,最近开发了各种检测结核病的技术。这些技术大大提高了结核病检测的可靠性和精确性。在结核病最易治疗的早期发现结核病仍然是一项挑战。为了提高胸部x线图像的分辨率,以便早期发现结核病,目前正在进行这方面的研究。本文建议使用Sovereign critic Network (SCN)模型从低分辨率x射线图像生成超分辨率图像。在TB胸片数据库中对建议的SCN模型分别进行超分辨率因子2、4和6的评价,其PSNR值分别为31.85、33.79和35.93,SSIM值分别为0.84、0.91和0.96。所提出的模型比现有的任何模型都显示出令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sovereign Critique Network (SCN) Based Super-Resolution for chest X-rays images
A prevalent and serious illness that affects people all over the globe is tuberculosis. A successful diagnosis of tuberculosis is essential for better survival rates and a successful course of treatment. Different techniques for detecting tuberculosis have been developed recently as a result of advancements in medical technology. These techniques have greatly increased the reliability and precision of tuberculosis detection. Finding tuberculosis at an early state, in which it is most treatable, is still a challenge. In order to improve the resolution of X-ray chest images for the early detection of tuberculosis, study is currently being done in this area. The Sovereign Critique Network (SCN) model is suggested in this article as a means of generating super resolution images from low-resolution X-ray images. The suggested SCN model is evaluated on the Tuberculosis (TB) Chest X-ray database for super resolution factors of 2, 4, and 6 separately with PSNR values of 31.85, 33.79, and 35.93 and SSIM values of 0.84, 0.91, and 0.96 for super resolution factors 2, 4, and 6, respectively. The proposed model shows promising results than any of the existing models.
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