M-sequence-coded excitation for magneto-acoustic imaging
- 41 Downloads
Magneto-acoustic imaging is a novel functional imaging method to electrical characteristics of tissue. It provides valuable tools for diagnosing early stage tumor and monitoring bioelectrical current. Common single short-pulse excitation limits SNR due to the short-pulse duration and low power of magneto-acoustic signal. In this study, we propose M-sequence-coded excitation and pulse compression approach to improve SNR of magneto-acoustic imaging. Simulations on the magneto-acoustic signal under different bit lengths M-sequence-coded excitation are performed. Experiments on the samples made of pork and graphite slices are done to validate the proposed coded excitation method. The SNR and sidelobe levels were investigated. The results showed when 7, 15, 31, 63, 127 bits M-sequence-coded excitations were applied onto the samples, SNR was improved by 17.4 dB, 24.2 dB, 30.6 dB, 37.6 dB, and 40.1 dB, respectively. For a similar SNR improvement, the total used time under coded excitation can be shortened to 9.4% under the single pulse excitation. The result indicates the M-sequence-coded excitation approach is effective to improve the magneto-acoustic signal SNR and shorten the imaging time.
KeywordsMagneto-acoustic imaging M-sequence code Signal-to-noise ratio (SNR) Pulse compression
Z Liu would like to thank Dr. Cheng Yi for his assistance in editing the language of this manuscript.
This study was supported by the Grants from the National Natural Foundation of China (61501523, 81772004), CAMS Initiative for Innovative Medicine (2017-I2M- 3-020), and National Natural Foundation of Tianjin (17JCZDJC32400).
- 10.Leo M, Hu G, He B (2014) Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet. Med Phys 41(2):131–134Google Scholar
- 13.Graslandmongrain P, Mari JM, Chapelon JY, Lafon C (2014) Lorentz force electrical impedance tomography. IRBM 34(4–5):357–360Google Scholar
- 15.Zhang S, Zhou X, Ma R, Yin T, Liu Z (2015) A study on locating the sonic source of sinusoidal magneto-acoustic signals using a vector method. Biomed Mater Eng 26(s1):1177–1184Google Scholar
- 19.Jibiki T (2001) Coded excitation medical ultrasound imaging. Jap J Med Phys 21(3):136–141Google Scholar
- 20.Golomb SW, Gong G (2005) Signal Design for Good Correlation: For Wireless Communication, Cryptography, and Radar. Cambridge University Press, U.K, pp 117–161Google Scholar
- 21.Xu Y, He B (2005) Magnetoacoustic tomography with magnetic induction (MAT-MI). IEEE Trans Med Imaging 29(10):3173–3176Google Scholar
- 25.Marcolin MA, Padberg F (2007) Transcranial brain stimulation for treatment in mental disorders. Adv Biol Psychiatry 23:204–225Google Scholar
- 26.Feng X, Gao F, Kishor R, Zheng Y (2014) Coexisting and mixing phenomena of thermoacoustic and magnetoacoustic waves in water. Sci Rep 5:1–10Google Scholar
- 29.Yu M, Zhang C, Yu G (2014) Research on a new waveform based on MAC sequence. In: 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Guilin, China, AUG, pp 456–460Google Scholar