A Noise Reduction Method for Photoacoustic Imaging <italic>In Vivo</italic> Based on EMD and Conditional Mutual Information

Abstract

Photoacoustic tomography is a technique to reconstruct the image of light energy absorption distribution in tissues based on the detected photoacoustic signals. In recent years, this research field has been greatly developed, and its application range is wide, including anatomy, functionality, and molecular imaging. However, the conversion efficiency of photoacoustic effect from light to sound is quite low, which leads to the low signal-to-noise ratio of photoacoustic signal and the poor quality of reconstructed photoacoustic image. The traditional method to improve the signal-to-noise ratio of photoacoustic signals is data averaging method, but it seriously limits the imaging speed due to multiple acquisition. Without sacrificing signal fidelity and imaging speed, an empirical mode decomposition (EMD) combined with conditional mutual information de-noising algorithm for photoacoustic tomography is proposed in this paper. The simulation results and experimental results of photoacoustic signal de-noising achieve significant improvement of signal-to-noise ratio of photoacoustic signal and the enhancement of contrast of the reconstructed image. The simulation results and experimental results show that EMD combined with mutual information method improves at least 2 dB and 3 dB, respectively, more than traditional wavelet threshold method and band-pass filter. The improvement of contrast-to-noise ratio is more than 2 dB and 3 dB, respectively, more than traditional wavelet threshold method and band-pass filter.

An Improved Denoising Method for Partial Discharge Signals Contaminated by White Noise Based on Adaptive Short-Time Singular Value Decomposition

“…The only parameter that needs to be preselected in the ASTSVD method is the sliding window length. To compare the denoising effect of ASTSVD with different sliding window lengths, two parameters, including the mean square error (MSE) [40,41] and normalized correlation coefficient (NCC) [42,43] were used to evaluate the performance of the ASTSVD. MSE and NCC are defined as Figure 6.…”

Photoacoustic image improvement based on a combination of sparse coding and filtering

“…The combination of these different types of noise in the PA signal leads to a low signal-to-noise ratio (SNR) and results in a poor quality reconstructed PA image. [27][28][29][30] Several previously reported studies have attempted to improve the image reconstruction algorithms to achieve noise-and artifact-free PA images. However, acquiring high-quality PA images from noisy signals requires an effective denoising technique, [31][32][33][34][35][36] prior to utilizing reconstruction algorithms.…”

“…37 However, the signal averaging method needs to acquire multiple frames, which is time-consuming and affects the frame rate of PA imaging. 29 Alternatively, the adaptive filtering method without any prior knowledge requirement was proposed for low-energy pulse laser diodes PA signal enhancement. 28 They average fewer frames, in comparison with conventional averaging techniques, which leads to shorter acquisition time.…”

Widefield illumination photoacoustic imaging of blood vessel phantom

“…Alongside conventional optical imaging modalities such as diffuse optical tomography and optical coherence tomography, PA imaging, also known as optoacoustic imaging, can overcome the limitations of shallow imaging depth or optical diffusion in highly turbid media, as well as provide a solution to the problem of low image contrast because of speckle artifacts, which is associated with the abovementioned solely optical imaging modalities . The latter advantage is a result of the detection of mechanical changes or ultrasonic waves as pressure signals, which are produced by thermoelastic expansion in the target objects upon the absorption of short‐pulsed laser beams, dependent on the laser wavelength . In this article, we present the demonstration of a simple and efficient PA imaging system, introducing widefield expanded‐laser‐beam illumination that fully covers the sample area of interest, in contrast to illumination based on point or focused sources .…”

“…3,4 The latter advantage is a result of the detection of mechanical changes or ultrasonic waves as pressure signals, which are produced by thermoelastic expansion in the target objects upon the absorption of short-pulsed laser beams, dependent on the laser wavelength. 5,6 In this article, we present the demonstration of a simple and efficient PA imaging system, introducing widefield expanded-laser-beam illumination that fully covers the sample area of interest, in contrast to illumination based on point or focused sources. 7,8 A filtered back-projection image-reconstruction algorithm was applied to the PA signals collected from a single transducer with a circular scanning receiver system.…”