Engineering Research Center of Molecular and Neuro Imaging of Ministry of China, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China.
Department of Ultrasound, Xian Chest Hospital, Xi'an, Shaanxi, China.
Med Biol Eng Comput. 2020 Jan;58(1):131-141. doi: 10.1007/s11517-019-02069-9. Epub 2019 Nov 21.
Cerenkov luminescence imaging(CLI) is an emerging molecular imaging technology able to optically visualize radioactive decay signals from medical isotopes and has found wide application in tumor diagnose, cancer therapy, drug development, intraoperative guidance, and so on. When Cerenkov luminescence data are collected, the high-energy particles from the radioactive nucleus will be detected by the sensitive CCD camera and lead to impulse noise. To suppress the impulse noise and improve the contrast of the useful signal to the background, the detection-based fuzzy switching median filtering framework is proposed in this paper. Several experiments were conducted respectively to investigate the statistical feature of the noise and to evaluate the performance of the proposed noise removal framework. The results show that the signal-to-noise ratio is improved after noise elimination. The proposed filtering framework outperforms the classical median filter in terms of root mean squared error and the structural similarity index. It also preserves the maximum value and the mean value in the regions of interest better than the median filter does. In addition, compared with the FLICMCDD algorithm, the proposed method works much faster while getting similar results. Graphical abstract.
切伦科夫发光成像（CLI）是一种新兴的分子成像技术，能够光学可视化放射性核素衰变信号，在肿瘤诊断、癌症治疗、药物开发、术中指导等方面得到了广泛应用。当收集切伦科夫发光数据时，放射性核的高能粒子将被敏感的 CCD 相机检测到，并导致脉冲噪声。为了抑制脉冲噪声并提高有用信号与背景的对比度，本文提出了基于检测的模糊开关中值滤波框架。分别进行了几项实验以研究噪声的统计特征，并评估所提出的噪声消除框架的性能。结果表明，噪声消除后信噪比得到了提高。与经典中值滤波器相比，所提出的滤波框架在均方根误差和结构相似性指数方面表现更好。它还比中值滤波器更好地保留了感兴趣区域中的最大值和平均值。此外，与 FLICMCDD 算法相比，该方法在获得相似结果的同时速度更快。
