The demand of the fast acquisition in 3D ultrasound (3D-US) imaging leads to the dense population of speckle noise which causes the difficulty in medical diagnosis. In this Letter, 3Dadaptive regularisation Savitzky–Golay (3D ARSG) filter is proposed as the real-time filter for removing speckle noise in 3D-US imaging. The 3D ARSG filter uses the local intensity homogeneity to classify between noisy and texture regions. The intensity in the noisy regions is heavily smoothed, while the resolvable edges remain sharp. The experiment on the denoising of the 3D simulated models and the 3D-US images indicated that 3D ARSG filter provided the image with far less noise and crisper objects’ boundary than conventional methods. In addition, the proposed filter preserves the structural details with regard to the dimension and can denoise images in real time.

References

1. 1)
  - 5. Toonkum, P., Boonvisut, P., Chinrungrueng, C.: ‘Real-time speckle reduction of ultrasound images based on regularized Savitzky–Golay filters’. The 2nd Int. Conf. on Bioinformatics and Biomedical Engineering, ICBBE 2008, May 2008, pp. 2311–2314.
2. 2)
  - 3. Huang, Q., Zheng, Y., Lu, M., Wang, T., Chen, S.: ‘A new adaptive interpolation algorithm for 3D ultrasound imaging with speckle reduction and edge preservation’, Comput. Med. Imaging Graph., 2009, 33, (2), pp. 100–110 (doi: 10.1016/j.compmedimag.2008.10.006).
3. 3)
  - 1. Govindan, P., Wang, B., Ravi, P., Saniie, J.: ‘Hardware and software architectures for computationally efficient three-dimensional ultrasonic data compression’, Circ. Dev. Syst., 2016, 10, (1), pp. 54–61 (doi: 10.1049/iet-cds.2015.0083).
4. 4)
  - 6. Toonkum, P., Suwanwela, N.C., Chinrungrueng, C.: ‘Reconstruction of 3D ultrasound images based on Cyclic Regularized Savitzky–Golay filters’, Ultrasonics, 2011, 51, (2), pp. 136–147 (doi: 10.1016/j.ultras.2010.07.003).
5. 5)
  - 7. Kwon, K., Kim, M., Shin, B.: ‘A fast 3D adaptive bilateral filter for ultrasound volume visualization’, Comput. Methods Programs Biomed., 2016, 133, pp. 25–34 (doi: 10.1016/j.cmpb.2016.05.008).
6. 6)
  - 8. Chen, Y., Yin, R., Flynn, P.J., Broschat, S.L.: ‘Aggressive region growing for speckle reduction in ultrasound images’, Pattern Recognit. Lett., 2003, 24, (4–5), pp. 677–691 (doi: 10.1016/S0167-8655(02)00174-5).
7. 7)
  - 2. Ponomaryov, V., Gallegos-Funes, F., Sansores-Pech, R., Sadovnychiy, S.: ‘Real-time noise suppression in 3D ultrasound imaging based on order statistics’, Electron. Lett., 2006, 42, (2), pp. 80–82 (doi: 10.1049/el:20063282).
8. 8)
  - 4. Chinrungrueng, C., Suvichakorn, A.: ‘Fast edge-preserving noise reduction for ultrasound images’, IEEE Trans. Nucl. Sci., 2001, 48, (3), pp. 849–854 (doi: 10.1109/23.940174).
9. 9)
  - 25. Zhou, W., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: ‘Image quality assessment: from error visibility to structural similarity’, IEEE Trans. Image Process., 2004, 13, (4), pp. 600–612 (doi: 10.1109/TIP.2003.819861).
10. 10)
  - 10. Eltoft, T.: ‘Modeling the amplitude statistics of ultrasonic images’, IEEE Trans. Med. Imaging, 2006, 25, (2), pp. 229–240 (doi: 10.1109/TMI.2005.862664).

Real-time 3D ultrasound denoising based on adaptive regularisation Savitzky–Golay filter

References

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