Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation

A crucial limitation of current high-resolution 3D photoacoustic tomography (PAT) devices that employ sequential scanning is their long acquisition time. In previous work, we demonstrated how to use compressed sensing techniques to improve upon this: images with good spatial resolution and contrast can be obtained from suitably sub-sampled PAT data acquired by novel acoustic scanning systems if sparsity-constrained image reconstruction techniques such as total variation regularization are used. Now, we show how a further increase of image quality can be achieved for imaging dynamic processes in living tissue (4D PAT). The key idea is to exploit the additional temporal redundancy of the data by coupling the previously used spatial image reconstruction models with sparsity-constrained motion estimation models. While simulated data from a two-dimensional numerical phantom will be used to illustrate the main properties of this recently developed joint-image-reconstruction-and-motion-estimation framework, measured data from a dynamic experimental phantom will also be used to demonstrate their potential for challenging, large-scale, real-world, three-dimensional scenarios. The latter only becomes feasible if a carefully designed combination of tailored optimization schemes is employed, which we describe and examine in more detail

Approximate k-space models and Deep Learning for fast photoacoustic reconstruction

We present a framework for accelerated iterative reconstructions using a fast and approximate forward model that is based on k-space methods for photoacoustic tomography. The approximate model introduces aliasing artefacts in the gradient information for the iterative reconstruction, but these artefacts are highly structured and we can train a CNN that can use the approximate information to perform an iterative reconstruction. We show feasibility of the method for human in-vivo measurements in a limited-view geometry. The proposed method is able to produce superior results to total variation reconstructions with a speed-up of 32 times

Developing Real-Time Implementations of Non-Linear Beamformers for Enhanced Optical Ultrasound Imaging

Free-hand optical ultrasound (OpUS) imaging is an emerging ultrasound imaging paradigm that utilises an array of fiber-optic sources and a single fiber-optic detector to achieve video-rate, real-time imaging with a flexible probe that is immune to electromagnetic interference. Due to the use of only a single detector, such probes have limited channel counts, resulting in significant imaging artefacts and limited contrast when imaging is performed with a conventional Delay-and-Sum (DAS) beamformer. Non-linear beamforming can help improve the imaging quality by exploiting cross-channel coherence across the aperture, at the expense of significantly increased computational complexity. In this work, GPU implementations of different non-linear beamformers were implemented and tailored specifically to OpUS array devices and tested on both simulated and experimental data

Accelerated High-Resolution Photoacoustic Tomography via Compressed Sensing

Current 3D photoacoustic tomography (PAT) systems offer either high image quality or high frame rates but are not able to deliver high spatial and temporal resolution simultaneously, which limits their ability to image dynamic processes in living tissue. A particular example is the planar Fabry-Perot (FP) scanner, which yields high-resolution images but takes several minutes to sequentially map the photoacoustic field on the sensor plane, point-by-point. However, as the spatio-temporal complexity of many absorbing tissue structures is rather low, the data recorded in such a conventional, regularly sampled fashion is often highly redundant. We demonstrate that combining variational image reconstruction methods using spatial sparsity constraints with the development of novel PAT acquisition systems capable of sub-sampling the acoustic wave field can dramatically increase the acquisition speed while maintaining a good spatial resolution: First, we describe and model two general spatial sub-sampling schemes. Then, we discuss how to implement them using the FP scanner and demonstrate the potential of these novel compressed sensing PAT devices through simulated data from a realistic numerical phantom and through measured data from a dynamic experimental phantom as well as from in-vivo experiments. Our results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction methods that describe the tissues structures with suitable sparsity-constraints are used. In particular, we examine the use of total variation regularization enhanced by Bregman iterations. These novel reconstruction strategies offer new opportunities to dramatically increase the acquisition speed of PAT scanners that employ point-by-point sequential scanning as well as reducing the channel count of parallelized schemes that use detector arrays.Comment: submitted to "Physics in Medicine and Biology

Contrast agents for molecular photoacoustic imaging.

Photoacoustic imaging (PAI) is an emerging tool that bridges the traditional depth limits of ballistic optical imaging and the resolution limits of diffuse optical imaging. Using the acoustic waves generated in response to the absorption of pulsed laser light, it provides noninvasive images of absorbed optical energy density at depths of several centimeters with a resolution of ∼100 μm. This versatile and scalable imaging modality has now shown potential for molecular imaging, which enables visualization of biological processes with systemically introduced contrast agents. Understanding the relative merits of the vast range of contrast agents available, from small-molecule dyes to gold and carbon nanostructures to liposome encapsulations, is a considerable challenge. Here we critically review the physical, chemical and biochemical characteristics of the existing photoacoustic contrast agents, highlighting key applications and present challenges for molecular PAI.This work was supported by CRUK (Career Establishment Award no. C47594/A16267 to J.W. and S.E.B., Core Funding C14303/A17197 to J.W. and S.E.B.), the European Commission (CIG FP7-PEOPLE- 2013-CIG-630729 to J.W. and S.E.B.), the EPSRC-CRUK Cancer Imaging Centre in Cambridge and Manchester (C197/A16465 to J.W. and S.E.B.), King’s College London and University College London Comprehensive Cancer Imaging Centre Cancer Research UK & Engineering and Physical Sciences Research Council, in association with the Medical Research Council and the Department of Health, UK (P.B.), and the European Union (project FAMOS FP7 ICT, contract 317744 to P.B.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nmeth.392

Model based learning for accelerated, limited-view 3D photoacoustic tomography

Recent advances in deep learning for tomographic reconstructions have shown great potential to create accurate and high quality images with a considerable speed-up. In this work we present a deep neural network that is specifically designed to provide high resolution 3D images from restricted photoacoustic measurements. The network is designed to represent an iterative scheme and incorporates gradient information of the data fit to compensate for limited view artefacts. Due to the high complexity of the photoacoustic forward operator, we separate training and computation of the gradient information. A suitable prior for the desired image structures is learned as part of the training. The resulting network is trained and tested on a set of segmented vessels from lung CT scans and then applied to in-vivo photoacoustic measurement data

Special Section Guest Editorial: Celebrating the Exponential Growth of Optoacoustic/Photoacoustic Imaging

Guest editors introduce contributors to the Special Section Celebrating the Exponential Growth of Optoacoustic/Photoacoustic Imaging. We are pleased to introduce the contributions to this JBO Special Section entitled “Celebrating the Exponential Growth of Biomedical Optoacoustic/Photoacoustic Imaging.” This title was chosen to reflect the strong growth of the field over the last two and a half decades. The diversity of papers in this special section bears witness to this, with contributions that encompass numerical modelling, advanced instrumentation, functional imaging, clinical translation, and novel biomedical applications

"I can decide to use the property I have to make money": HIV vulnerability of bar workers and bar patrons in Kumasi, Ghana

This study was implemented by Boston University in collaboration with the Kwame Nkrumah University of Science and Technology with support from the President’s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Agency for International Development under Project SEARCH Task Order No. GHH‐I‐00‐07‐00023‐00, beginning August 27, 2010. The content and views expressed here are the authors’ and do not necessarily reflect the opinion or policy of USAID or the U.S. Government.This report provides the findings from a qualitative study exploring the social, economic and behavioral vulnerability to HIV of women working in bars and restaurants in Kumasi, Ghana’s second largest city. This research was conducted by a collaborative team comprised of researchers from Boston University’s Center for Global and Health and Development (CGHD) and the Kwame Nkrumah University of Science and Technology (KNUST) School of Medical Sciences. It is one of nine studies under the Operations Research on Key Populations project funded by the United States Agency for International Development (USAID). The study was designed and carried out in collaboration with the Ghana AIDS Commission (GAC). Reducing vulnerability to HIV infection among key populations in Ghana is a major goal for the National AIDS Control Program (NACP) and the GAC. While a number of studies have explored HIV risk behaviours among self-identified female sex workers and their partners in Ghana, little is known about the vulnerability of women working in small bars and restaurants who may be involved in transactional sex. Further, we have little information about how best to reach this population with services that will enable them and their clientele to protect themselves from HIV and reduce other vulnerabilities related to their health and well-being. To address this gap, this study aimed to explore behavioural, social, and economic factors that contribute to HIV vulnerability; types and extent of transactional sex; the relationship between alcohol/drug use, unsafe sex and transactional sex; and the health and social service needs of this population. The study findings are meant to inform the development and implementation of HIV prevention programs for bar workers and bar patrons.Support from the President’s Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Agency for International Development under Project SEARCH Task Order No. GHH‐I‐00‐07‐00023‐00, beginning August 27, 201