Numerical analysis of ultrasound propagation and reflection intensity for biological acoustic impedance microscope

Agus Indra Gunawan, Naohiro Hozumi, Sachiko Yoshida, Yoshifumi Saijo, Kazuto Kobayashi, Seiji Yamamoto

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)


Abstract This paper proposes a new method for microscopic acoustic imaging that utilizes the cross sectional acoustic impedance of biological soft tissues. In the system, a focused acoustic beam with a wide band frequency of 30-100 MHz is transmitted across a plastic substrate on the rear side of which a soft tissue object is placed. By scanning the focal point along the surface, a 2-D reflection intensity profile is obtained. In the paper, interpretation of the signal intensity into a characteristic acoustic impedance is discussed. Because the acoustic beam is strongly focused, interpretation assuming vertical incidence may lead to significant error. To determine an accurate calibration curve, a numerical sound field analysis was performed. In these calculations, the reflection intensity from a target with an assumed acoustic impedance was compared with that from water, which was used as a reference material. The calibration curve was determined by changing the assumed acoustic impedance of the target material. The calibration curve was verified experimentally using saline solution, of which the acoustic impedance was known, as the target material. Finally, the cerebellar tissue of a rat was observed to create an acoustic impedance micro profile. In the paper, details of the numerical analysis and verification of the observation results will be described.

Original languageEnglish
Article number5027
Pages (from-to)79-87
Number of pages9
Publication statusPublished - 2015 Aug 1


  • Acoustic impedance
  • Plane wave
  • Tissue
  • Ultrasound
  • k-space


Dive into the research topics of 'Numerical analysis of ultrasound propagation and reflection intensity for biological acoustic impedance microscope'. Together they form a unique fingerprint.

Cite this