一种新的X射线图像增强方法,使用分数微分方程类
Rasha Saad Aldoury1, Nadia M G Al-Saidi2, Rabha W Ibrahim3,4,5
1Department of Radiology Techniques, AL-Salam University College, Baghdad, 10064, Iraq.
MethodsX
|July 3, 2023
概括
这项研究使用k-Caputo分数微分运算符 (K-CFDO) 增强了医疗X射线图像,以提高清晰度和细节. K-CFDO方法提高了图像质量,有助于诊断,并可能提高农村环境中的医疗保健效率.
科学领域:
- 医疗成像医学成像
- 图像处理 图像处理
- 应用数学 应用数学 应用数学
背景情况:
- 医疗图像质量对于诊断至关重要,但通常会因噪音和低对比度而降低.
- 医疗图像的增强带来了挑战,原因是捕获的数据中不可预测的变化.
- 医生需要高对比度的图像,以便详细的可视化疾病和准确的治疗计划.
研究的目的:
- 提高医学图像的视觉质量,特别是X射线,使用一种新的图像增强技术.
- 为了确定图像像素的能量,提高像素强度和更好的对比度.
- 为了捕捉高频细节并保持精细的图像结构.
主要方法:
- 该研究使用基于k-卡普托分数微分演算子 (K-CFDO) 的概括k-微分方程.
- K-CFDO用于分析像素能量和增强图像对比度,特别用于低对比度X射线图像.
- 该方法利用像素概率来捕捉高频细节,同时保持图像完整性.
主要成果:
- 通过K-CFDO方法,图像质量得到了改善,如胸部和牙X射线的Brisque,Niqe和Piqe得分降低.
- 量化结果显示,胸部X射线的平均Brisque,Niqe和Piqe值为 (23.25,2.8,21.58),牙X射线的平均值为 (21.12,3.77,23.49).
- 增强方法成功地改善了医疗图像中的视觉细节.
结论:
- 拟议的基于K-CFDO的图像增强方法显示了改善医疗图像质量的潜力.
- 增强的图像细节可以帮助医疗人员进行诊断过程,提高临床决策的效率和准确性.
- 该研究确定了图像过度增强是由于参数设置不正确而造成的限制,这表明了未来研究的领域.
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