A deep learning approach for the fast generation of acoustic holograms

Programmable Acoustic Holography using Medium-Sound-Speed Modulation

Acoustic holography offers the ability to generate designed acoustic fields to manipulate microscale objects. However, the static nature or large aperture sizes of 3D printed acoustic holographic phase plates limits the ability to rapidly alter generated fields. In this work， a programmable acoustic holography approach is demonstrated by which multiple discrete or continuously variable acoustic targets can be created. Here, the holographic phase plate encodes multiple images, where the desired field is produced by modifying the sound speed of an intervening fluid media. Its flexibility is demonstrated in generating various acoustic patterns, including continuous line segments, discrete letters and numbers, using this method as a sound speed indicator and fluid identification tool. This programmable acoustic holography approach has the advantages of generating reconfigurable and designed acoustic fields, with broad potential in microfluidics, cell/tissue engineering, real-time sensing, and medical ultrasound.

Multi-frequency acoustic hologram generation with a physics-enhanced deep neural network

Here, a physics-enhanced multi-frequency acoustic hologram deep neural network (PhysNet_MFAH) method is proposed for designing multi-frequency acoustic holograms, which is built by incorporating multiple physical models that represent the physical processes of acoustic waves propagation for a set of design frequencies into a deep neural network. It is demonstrated that one needs only to feed a set of frequency-specific target patterns into the network, the proposed PhysNet_MFAH method can automatically, accurately, and rapidly generate a high-quality multi-frequency acoustic hologram for holographic rendering of different target acoustic fields in the same or distinct regions of the target plane when driven at different frequencies. Remarkably, it is also demonstrated that the proposed PhysNet_MFAH method can achieve a higher quality of the reconstructed acoustic intensity fields than the existing optimization methods IASA and DS for designing multi-frequency acoustic holograms at a relatively fast-computational speed. Furthermore, the performance dependencies of the proposed PhysNet_MFAH method on different design parameters are established, which provide insight into the performance of the reconstructed acoustic intensity fields when subject to different design conditions of the proposed PhysNet_MFAH method. We believe that the proposed PhysNet_MFAH method can facilitate many potential applications of acoustic holograms, ranging from dynamic particle manipulation to volumetric display.

Deep Learning-Based Framework for Fast and Accurate Acoustic Hologram Generation

Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and medical imaging. However, only a few studies on how to generate acoustic holograms have been conducted, and even conventional acoustic hologram algorithms show limited performance in the fast and accurate generation of acoustic holograms, thus hindering the development of novel applications. We here propose a deep learning-based framework to achieve fast and accurate acoustic hologram generation. The framework has an autoencoder-like architecture; thus, the unsupervised training is realized without any ground truth. For the framework, we demonstrate a newly developed hologram generator network, the holographic ultrasound generation network (HU-Net), which is suitable for unsupervised learning of hologram generation, and a novel loss function that is devised for energy-efficient holograms. Furthermore, for considering various hologram devices (i.e., ultrasound transducers), we propose a physical constraint (PC) layer. Simulation and experimental studies were carried out for two different hologram devices, such as a 3-D printed lens, attached to a single element transducer, and a 2-D ultrasound array. The proposed framework was compared with the iterative angular spectrum approach (IASA) and the state-of-the-art (SOTA) iterative optimization method, Diff-PAT. In the simulation study, our framework showed a few hundred times faster generation speed, along with comparable or even better reconstruction quality, than those of IASA and Diff-PAT. In the experimental study, the framework was validated with 3-D printed lenses fabricated based on different methods, and the physical effect of the lenses on the reconstruction quality was discussed. The outcomes of the proposed framework in various cases (i.e., hologram generator networks, loss functions, and hologram devices) suggest that our framework may become a very useful alternative tool for other existing acoustic hologram applications, and it can expand novel medical applications.

Theoretical Zero-Thickness Broadband Holograms Based on Acoustic Sieve Metasurfaces

Acoustic holography is an essential tool for controlling sound waves, generating highly complex and customizable sound fields, and enabling the visualization of sound fields. Based on acoustic sieve metasurfaces (ASMs), this paper proposes a theoretical design approach for zero-thickness broadband holograms. The ASM is a zero-thickness rigid screen with a large number of small holes that allow sound waves to pass through and produce the desired real image in the target plane. The hole arrangement rules are determined using a genetic algorithm and the Rayleigh–Sommerfeld theory. Because the wave from a hole has no extra phase or amplitude modulation, the intractable modulation dispersion can be physically avoided, allowing the proposed ASM-based hologram to potentially function in any frequency band as long as the condition of paraxial approximation is satisfied. Using a numerical simulation based on the combination of the finite element method (FEM) and the boundary element method (BEM), this research achieves broadband holographic imaging with a good effect. The proposed theoretical zero-thickness broadband hologram may provide new possibilities for acoustic holography applications.