Noise reduction algorithm based on wavelet transform and its effect on efficient pileup correction algorithms for digital gamma ray spectroscopy

A novel noise reduction algorithm combined with compressive sensing (CS) and lifting wavelet transform (LWT) is proposed in this paper. This algorithm can overcome the limitations of traditional noise reduction methods based on Kalman filtering and wavelet threshold filtering. The characteristics of wavelet time-frequency distribution of the microelectromechanical system (MEMS) gyroscope are discussed to illustrate the demerit of the classical filtering methods. Noise reduction algorithm of MEMS gyroscope signal is studied in detail by combining CS theory with lifting wavelet transform. De-noising effect, time-consumption of computation as well as traditional CS reconstruction algorithms are analyzed. The results show that the signal reconstruction algorithm of conventional matching pursuit (MP) greedy algorithms contains more glitches and computation time-consumption, the basis pursuit de-noising (BPDN) algorithm is better and it has advantages of high computational efficiency and ease of implementation.

Download Full-text

Evaluation of the image quality and dose reduction in digital radiography with an advanced spatial noise reduction algorithm in pediatric patients

European Radiology ◽

10.1007/s00330-021-07942-6 ◽

2021 ◽

Author(s):

Saelin Oh ◽

Ji Hye Kim ◽

So-Young Yoo ◽

Tae Yeon Jeon ◽

Yu Jin Kim

Keyword(s):

Image Quality ◽

Noise Reduction ◽

Dose Reduction ◽

Digital Radiography ◽

Pediatric Patients ◽

Reduction Algorithm ◽

Spatial Noise ◽

Noise Reduction Algorithm

Download Full-text

Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽

10.3390/diagnostics11020319 ◽

2021 ◽

Vol 11 (2) ◽

pp. 319

Author(s):

Chan-Rok Park ◽

Seong-Hyeon Kang ◽

Young-Jin Lee

Keyword(s):

Image Quality ◽

Noise Reduction ◽

Total Variation ◽

Parallel Imaging ◽

Pulse Sequence ◽

Reduction Algorithm ◽

Median Filters ◽

Reduction Techniques ◽

Imaging Results ◽

Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

Download Full-text