Macro-mechanics controls quantum mechanics: mechanically controllable quantum conductance switching of an electrochemically fabricated atomic-scale point contact.

Here, we present a silver atomic-scale device fabricated and operated by a combined technique of electrochemical control (EC) and mechanically controllable break junction (MCBJ). With this EC-MCBJ technique, we can perform mechanically controllable bistable quantum conductance switching of a silver quantum point contact (QPC) in an electrochemical environment at room temperature. Furthermore, the silver QPC of the device can be controlled both mechanically and electrochemically, and the operating mode can be changed from 'electrochemical' to 'mechanical', which expands the operating mode for controlling QPCs.

Optoacoustic image segmentation based on signal domain analysis.

Efficient segmentation of optoacoustic images has importance in enhancing the diagnostic and quantification capacity of this modality. It may also aid in improving the tomographic reconstruction accuracy by accounting for heterogeneous optical and acoustic tissue properties. In particular, when imaging through complex biological tissues, the real acoustic properties often deviate considerably from the idealized assumptions of homogenous conditions, which may lead to significant image artifacts if not properly accounted for.

High-Throughput Sparsity-Based Inversion Scheme for Optoacoustic Tomography.

The concept of sparsity is extensively exploited in the fields of data acquisition and image processing, contributing to better signal-to-noise and spatio-temporal performance of the various imaging methods. In the field of optoacoustic tomography, the image reconstruction problem is often characterized by computationally extensive inversion of very large datasets, for instance when acquiring volumetric multispectral data with high temporal resolution. In this article we seek to accelerate accurate model-based optoacoustic inversions by identifying various sources of sparsity in the forward and inverse models as well as in the single- and multi-frame representation of the projection data.

Efficient non-negative constrained model-based inversion in optoacoustic tomography.

The inversion accuracy in optoacoustic tomography depends on a number of parameters, including the number of detectors employed, discrete sampling issues or imperfectness of the forward model. These parameters result in ambiguities on the reconstructed image. A common ambiguity is the appearance of negative values, which have no physical meaning since optical absorption can only be higher or equal than zero.

Spatiospectral denoising framework for multispectral optoacoustic imaging based on sparse signal representation.

Purpose: One of the major challenges in dynamic multispectral optoacoustic imaging is its relatively low signal-to-noise ratio which often requires repetitive signal acquisition and averaging, thus limiting imaging rate. The development of denoising methods which prevent the need for signal averaging in time presents an important goal for advancing the dynamic capabilities of the technology.

Methods: In this paper, a denoising method is developed for multispectral optoacoustic imaging which exploits the implicit sparsity of multispectral optoacoustic signals both in space and in spectrum.

Real-time optoacoustic tomography of indocyanine green perfusion and oxygenation parameters in human finger vasculature.

We interrogated whether optoacoustic tomography could be employed to study blood functional parameters and biodistribution of injected fluorescent agents in humans. Using a multichannel scanner at a frame rate of 10 images per second, we obtained cross-sectional images of the human finger in real time, before and after the administration of indocyanine green. We demonstrated that multispectral optoacoustic tomography can sense fast flow kinetics and resolve spatiotemporal characteristics of a common fluorochrome in human vasculature at clinically relevant concentrations.

Expediting model-based optoacoustic reconstructions with tomographic symmetries.

Purpose: Image quantification in optoacoustic tomography implies the use of accurate forward models of excitation, propagation, and detection of optoacoustic signals while inversions with high spatial resolution usually involve very large matrices, leading to unreasonably long computation times. The development of fast and memory efficient model-based approaches represents then an important challenge to advance on the quantitative and dynamic imaging capabilities of tomographic optoacoustic imaging.

Methods: Herein, a method for simplification and acceleration of model-based inversions, relying on inherent symmetries present in common tomographic acquisition geometries, has been introduced.

Optoacoustic imaging and tomography: reconstruction approaches and outstanding challenges in image performance and quantification.

This paper comprehensively reviews the emerging topic of optoacoustic imaging from the image reconstruction and quantification perspective. Optoacoustic imaging combines highly attractive features, including rich contrast and high versatility in sensing diverse biological targets, excellent spatial resolution not compromised by light scattering, and relatively low cost of implementation. Yet, living objects present a complex target for optoacoustic imaging due to the presence of a highly heterogeneous tissue background in the form of strong spatial variations of scattering and absorption.