Radiography is a commonly used diagnostic tool in animal practice to provide clinical information. The recent market for animal radiography is rapidly growing owing to the increasing awareness of the welfare of companion animals and the expansion of animal clinics. As the clinical use of radiography in animal hospitals has grown rapidly, radiologists continuously seek ways to reduce the radiation dose to animals. This study proposes an effective noise removal method using a modified image pyramid with guided filtering and Bayesian shrinkage threshold for low-dose animal radiography. This study aims to model a modified image pyramid-based denoising algorithm and to confirm its applicability in an animal radiographic system. We conducted an experiment on a companion dog and cat using a commercially-available veterinary radiographic system and quantitatively evaluated the image quality using the peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The PSNR and SSIM values measured in the denoised image of the dog using the proposed denoising algorithm were 39.54 and 0.96, respectively, which are improvements of approximately 11.3% and 5.5% of the values obtained in the original noisy image. Consequently, the proposed method is highly efficient in reducing image noise in animal radiography, thereby improving the image quality.

中文翻译：

---

在低剂量动物射线照相中使用带有引导滤波和贝叶斯收缩阈值的改进图像金字塔来改善噪声特性

放射线照相术是动物实践中常用的诊断工具，可提供临床信息。由于人们对伴侣动物福利的认识不断提高以及动物诊所的扩张，近期动物放射成像市场正在迅速增长。随着放射成像在动物医院的临床应用迅速增长，放射科医生不断寻求减少动物辐射剂量的方法。本研究提出了一种有效的噪声去除方法，使用带有引导过滤和贝叶斯收缩阈值的修改图像金字塔，用于低剂量动物放射线照相。本研究旨在对改进的基于图像金字塔的去噪算法进行建模，并确认其在动物射线照相系统中的适用性。我们使用市售兽医射线照相系统对伴侣狗和猫进行了实验，并使用峰值信噪比（PSNR）和结构相似性（SSIM）定量评估图像质量。使用所提出的去噪算法在狗的去噪图像中测得的 PSNR 和 SSIM 值分别为 39.54 和 0.96，分别比原始噪声图像中获得的值提高了约 11.3% 和 5.5%。因此，所提出的方法可以高效地减少动物放射线摄影中的图像噪声，从而提高图像质量。