2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired...

Area of Science:

• Ultrasound imaging
• Array signal processing
• Computational electromagnetics

Background:

• Full matrix arrays in 3-D ultrasound require numerous individually controlled elements, posing a hardware challenge.
• Sparse array techniques reduce element count but necessitate precise optimization of element positions.
• Existing optimization methods may not adequately address multi-depth pressure field control.

Purpose of the Study:

• To introduce novel energy functions within the simulated annealing (SA) algorithm for optimizing sparse array element placement.
• To enhance 3-D ultrasound imaging by reducing the number of active transducer elements.
• To achieve precise control over the radiated pressure field at multiple depths.

Main Methods:

• Utilizing simulated annealing (SA) with new energy functions to optimize sparse array layouts.
• Simulating radiated patterns for element translation at each SA iteration.
• Developing energy functions inspired by Blackman-tapered spiral arrays to control main, side, and grating lobes.

Main Results:

• Optimized sparse array layouts demonstrate performance comparable or superior to reference spiral arrays.
• The influence of SA parameters (iterations, measurement points, depths) on layout optimization was analyzed.
• Novel energy functions effectively limit main lobe width and reduce side/grating lobe levels across depths.

Conclusions:

• The proposed SA-based optimization with novel energy functions offers an effective solution for sparse array design in 3-D ultrasound.
• This approach significantly reduces hardware complexity without compromising imaging quality.
• The method provides predictable optimization duration due to SA's finite-time convergence properties.