Single Pixel Imaging

June 13, 2023June 13, 2023

Single-detector 3D optoacoustic tomography via coded spatial acoustic modulation.

2022 Communications Engineering

Evgeny Hahamovich, Sagi Monin, Ahiad Levi, Yoav Hazan & Amir Rosenthal

Abstract
Optoacoustic tomography (OAT) is a hybrid imaging modality that combines optical excitation with ultrasound detection and enables high-resolution visualization of optical contrasts at tissue depths in which light is completely diffused. Despite its promise in numerous research and clinical applications, OAT is limited by the technological immaturity of ultrasound detection systems. It suffers from limited element count, narrow field of view and lack of technology for spatial modulation of acoustic signals. Here we report single-detector OAT capable of high-fidelity imaging using an amplitude mask in planar geometry coded with cyclic patterns for structured spatial acoustic modulation. Our image reconstruction method maximises sensitivity, is compatible with planar signal detection, and uses only linear operations, thus avoiding artefacts associated with the nonlinear compressed-sensing inversion. We demonstrate our method for 3D OAT of complex objects and living tissue performed with only a single ultrasound detector, effectively coded into a 2D array with 1763 elements. Our method paves the way for a new generation of high-fidelity, low-cost OAT systems.

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Fig. A is a photograph of the leg. B is a subset over a vertical line of the measured signals, C is the de-multiplexed signals, and D is the MAP of the reconstructed optical density as a function of depth (z). The amplitudes are in arbitrary units.

Evgeny Hahamovich, Sagi Monin, Ahiad Levi, Yoav Hazan & Amir Rosenthal

2022 Communications Engineering – https://doi.org/10.1038/s44172-022-00030-7

July 29, 2021July 29, 2021

Single pixel imaging at megahertz switching rates via cyclic Hadamard masks.

2021 nature communications

Abstract
Optical imaging is commonly performed with either a camera and wide-field illumination or with a single detector and a scanning collimated beam; unfortunately, these options do not exist at all wavelengths. Single-pixel imaging offers an alternative that can be performed with a single detector and wide-field illumination, potentially enabling imaging applications in which the detection and illumination technologies are immature. However, single-pixel imaging currently suffers from low imaging rates owing to its reliance on configurable spatial light modulators, generally limited to 22 kHz rates. We develop an approach for rapid single-pixel imaging which relies on cyclic patterns coded onto a spinning mask and demonstrate it for in vivo imaging of C. elegans worms. Spatial modulation rates of up to 2.4 MHz, imaging rates of up to 72 fps, and image-reconstruction times of down to 1.5 ms are reported, enabling real-time visualization of dynamic objects.

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a Video capturing of vertically shifted resolution target, 101 × 103 resolution and 72 fps frame rate. Total recording rate of 0.75 M pixels per second. Frames 1, 30, 60, 90, 110, and 142 out of the 142 captured frames are presented. The red and blue circles mark constant positions on the resolution target. b, c Videos capturing the motion of C. elegans worms at a frame rate of 10 fps, corresponding to a total recording rate of 0.7 M pixels per second. Frames 5, 10, 15, 20, 25, and 30 out of 31 frames are presented.

Evgeny Hahamovich*, Sagi Monin*, Yoav Hazan & Amir Rosenthal
*equal contribution

2021 nature communications – https://doi.org/10.1038/s41467-021-24850-x

July 29, 2021July 29, 2021

Single-pixel imaging of dynamic objects using multi-frame motion estimation.

2021 Scientific Reports

Abstract
Single-pixel imaging (SPI) enables the visualization of objects with a single detector by using a sequence of spatially modulated illumination patterns. For natural images, the number of illumination patterns may be smaller than the number of pixels when compressed-sensing algorithms are used. Nonetheless, the sequential nature of the SPI measurement requires that the object remains static until the signals from all the required patterns have been collected. In this paper, we present a new approach to SPI that enables imaging scenarios in which the imaged object, or parts thereof, moves within the imaging plane during data acquisition. Our algorithms estimate the motion direction from inter-frame cross-correlations and incorporate it in the reconstruction model. Moreover, when the illumination pattern is cyclic, the motion may be estimated directly from the raw data, further increasing the numerical efficiency of the algorithm. A demonstration of our approach is presented for both numerically simulated and measured data.

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Schematic of the two proposed algorithms (a) Flow of the algorithm in case of global motion. (b) Flow of algorithm in case of local motion..

Sagi Monin, Evgeny Hahamovich & Amir Rosenthal

2021 Scientific Reports – https://doi.org/10.1038/s41598-021-83810-z

July 6, 2020June 18, 2023

Ultrasound Detection Arrays Via Coded Hadamard Apertures.

Abstract
In the medical fields, ultrasound detection is often performed with piezoelectric arrays that enable one to simultaneously map the acoustic fields at several positions. In this work, we develop a novel method for transforming a single-element ultrasound detector into an effective detectionarray by spatially filtering the incoming acoustic fields using a binary acoustic mask coded with cyclic Hadamard patterns. By scanning the mask in front of the detector, we obtain a multiplexed measurement dataset from which a map of the acoustic field is analyticallyconstructed. We experimentally demonstrate our method by transforming a single-element ultrasound detector into 1D arrays with up to 59 elements.

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Fig. Normalized waveform shape comprasion of the strongest signal for a single vs. multiplexed aperture detection. The plots are for (a) an aperture with 1.5 mm diameter and 31 elements and (b) an aperture with 1 mm diameter and 59 elements.

E. Hahamovich and A. Rosenthal, “Ultrasound Detection Arrays Via Coded Hadamard Apertures,” in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, doi: 10.1109/TUFFC.2020.2993583.

December 17, 2018June 18, 2023

Ultrasound Detection Using Acoustic Apertures

Ultrasound detection is commonly performed by piezoelectric transducers that are optimized for a specific application. Since the piezoelectric technology is not configurable, transducers designed for one application may not be compatible with other applications. In addition, some designs of ultrasound transducers may be difficult to implement owing to production constraints. In this paper, we propose a simple, low-cost method to reconfigure the geometry of ultrasound transducers. The technique is based on using apertures in thin sheets of acoustic blockers. We experimentally demonstrate this method for an ultrasound transducer with a central frequency of 1 MHz and show that it can emulate detectors of various sizes. An added advantage of this technique is its capability to achieve semi-isotropic detection sensitivity due to diffraction when the aperture size is comparable to the acoustic wavelength even when the angular sensitivity of the transducer is inherently limited.[Read More…]

Fig. 1 (a) Side view illustration of the detection scheme used in this paper. An ultrasound blocking mask with an aperture is placed in front of a large-area ultrasound receiver, resulting in an emulated detector whose detection characteristics depend on the aperture geometry. (b) Illustration of the experimental setup in which the emulated detector was used to characterize the 2-D diffraction map from an ultrasound transmitter. (c) Illustration of the setup used for characterizing the angular sensitivity of the emulated detector. (b) and (c) Transmitter was scanned in the xy plane while keeping the same z value for the transmitter, the receiver, and the aperture mask centers.

E Hahamovich, A Rosenthal, “Ultrasound Detection Using Acoustic Apertures”,in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control ( Volume: 65 , Issue: 1 , Jan. 2018 )