Side lobe free medical ultrasonic imaging with application to assessing side lobe suppression filter
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When focusing using an ultrasonic transducer array, a main lobe is formed in the focal region of an ultrasound field, but side lobes also arise around the focal region due to the leakage. Since the side lobes cannot be completely eliminated in the focusing process, they are responsible for subsequent ultrasound image quality degradation. To improve ultrasound image quality, a signal processing strategy to reduce side lobes is definitely in demand. To this end, quantitative determination of main and side lobes is necessary. We propose a theoretically and actually error-free method of exactly discriminating and separately computing the main lobe and side lobe parts in ultrasound image by computer simulation. We refer to images constructed using the main and side lobe signals as the main and side lobe images, respectively. Since the main and side lobe images exactly represent their main and side lobe components, respectively, they can be used to evaluate ultrasound image quality. Defining the average brightness of the main and side lobe images, the conventional to side lobe image ratio, and the main to side lobe image ratio as image quality metrics, we can evaluate image characteristics in speckle images. The proposed method is also applied in assessing the performance of side lobe suppression filtering. We show that the proposed method may greatly aid in the evaluation of medical ultrasonic images using computer simulations, albeit lacking the use of actual experimental data.
KeywordsFilter evaluation Main lobe Side lobe Side lobe suppression Speckle Ultrasonic image
This work was supported by the Daejin University Research Grants in 2018.
Compliance with ethical standards
Conflict of interest
All authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- 1.Macovski A. Medical imaging systems. Englewood Cliffs: Prentice Hall; 1983.Google Scholar
- 7.Keitman-Curdes O, Brendel B, Marg C, Ermert H. Optimization of apodizations based on the sidelobe pressure energy in simulated ultrasound fields. In: Proceedings of IEEE Ultrasonics Symposium Conference; 2003. p. 1677–80.Google Scholar
- 15.Jeong MK, Kwon SJ. A novel side lobe estimation method in medical ultrasound imaging systems. In: Proceedings of IEEE Ultrasonics Symposium Conference; 2015.Google Scholar
- 17.Synnevåg JF, Austeng A, Holm S. Minimum variance adaptive beamforming applied to medical ultrasound imaging. In: Proceedings of IEEE Ultrasonics Symposium Conference; 2005. p. 1199–202.Google Scholar