HYDRODYNAMICS AND ACOUSTICS

2019 ◊ Volume 1 (91) ◊ Issue 4 ◊ p. 434-448

A. G. Rudnitskii^*, M. A. Rudnytska^*, L. V. Tkachenko^*

^* Institute of Hydromechanics of NAS of Ukraine, Kyiv, Ukraine

Preprocessing and enhancing image quality of tomography optoacoustic reconstruction

Gidrodin. akust. 2019, 1(4):434-448

TEXT LANGUAGE:English

ABSTRACT

The photoacoustic method offers excellent optical contrast combined with deep ultrasonic penetration and resolution for structural and functional medical imaging. In this work, we focus on designing the 3D filter for efficient and comprehensive suppression of different kinds of noises that could coexist in photoacoustic signals. We consider spatial filters with only one parameter to tune: the window size. The Median-Modified Wiener Filter (MMWF) and Iterative Truncated Arithmetic Mean Filter (ITM) were compared with well-established denoising techniques (Mean, Median, and Wiener Filters) to suggest the best approach to practical use. Their performance was tested using Shepp-Logan phantom of size 256x256x256 voxels. In addition to the visual quality, we considered the Signal-to-Noise Ratio (SNR), Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). Performance of the proposed filters was also assessed in terms of processing time. Simulation results reveal that the ITM and MMWF filters outperform the existing state of art filters by providing better visual quality along with PSNR, SSIM, and MSE values for the Shepp-Logan phantom corrupted by the Gaussian or impulse noise and the mix of these noises.

KEY WORDS

denoising, image processing, noise reduction filter, spatial filtering, photoacoustic imaging, fuzzy sets

REFERENCES