Shape Estimation Algorithm for Ultrasound Imaging by Flexible Array Transducer.

Area of Science:

• Medical imaging
• Biomedical engineering
• Acoustics

Background:

• Flexible ultrasound array transducers offer potential for continuous, unconstrained medical imaging.
• Accurate array shape estimation is crucial for high-quality ultrasound image reconstruction, particularly in delay-and-sum beamforming.
• Existing methods often rely on external devices, limiting unconstrained applications.

Purpose of the Study:

• To develop and validate an algorithm for estimating ultrasound array transducer shape using only backscattered ultrasound signals.
• To enable accurate shape estimation without external tracking devices for flexible ultrasound arrays.
• To improve the quality of ultrasound images generated by flexible transducers.

Main Methods:

• Proposed an algorithm based on minimizing image entropy, assuming higher accuracy in shape estimation leads to lower entropy.
• Utilized backscattered ultrasound signals for shape estimation, eliminating the need for external devices.
• Validated the algorithm through simulation experiments with varying transducer parameters and phantom experiments with commercial transducers.

Main Results:

• The algorithm successfully estimated array shapes for simulated and real-world transducers (linear, convex, concave).
• Achieved an average element position error of less than one-eighth of the transmitted signal's wavelength.
• Demonstrated sufficient accuracy for shape estimation, crucial for beamforming calculations.

Conclusions:

• The proposed entropy-based algorithm accurately estimates ultrasound array shapes from backscattered signals alone.
• This method has the potential to significantly enhance ultrasound image clarity with flexible array transducers.
• Enables long-term, continuous, and unconstrained ultrasound imaging applications.