Accelerated high-resolution photoacoustic tomography via compressed sensing

  title={Accelerated high-resolution photoacoustic tomography via compressed sensing},
  author={Simon Robert Arridge and Paul C. Beard and Marta M. Betcke and Benjamin T. Cox and Nam Huynh and Felix Lucka and Olumide Ogunlade and Edward Z. Zhang},
  journal={Physics in Medicine \& Biology},
  pages={8908 - 8940}
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 (4D PAT. [] Key Method We demonstrate that combining model-based, 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…

Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation

This work shows how a further increase of image quality or acquisition speed rate can be achieved for imaging dynamic processes in living tissue (4D PAT) by coupling the previously used spatial image reconstruction models with sparsity-constrained motion estimation models.

A framework for directional and higher-order reconstruction in photoacoustic tomography

This work presents a modular reconstruction framework for photoacoustic tomography, which enables easy comparisons between regularisers with different properties, e.g. nonlinear, higher-order or directional, and solves the underlying minimisation problem with an efficient first-order primal-dual algorithm.

Real-time photoacoustic projection imaging using deep learning

The proposed DALnet combines the universal backprojection using dynamic aperture length (DAL) correction with a deep convolutional neural network (CNN) that is capable of producing high-resolution projection images of 3D structures at a frame rate of over 50 images per second on a standard PC with NVIDIA TITAN Xp GPU.

Sparsity-Based Recovery of Three-Dimensional Photoacoustic Images from Compressed Single-Shot Optical Detection

This investigation proposes and models a method of volumetric PA imaging using a state-of-the-art compressed sensing approach to achieve real-time acquisition of the initial pressure distribution (IPD) at a reduced level of cost and complexity.

Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography

A deep neural network is presented that is specifically designed to provide high resolution 3-D images from restricted photoacoustic measurements to represent an iterative scheme and incorporates gradient information of the data fit to compensate for limited view artifacts.

Enhancing sparse-view photoacoustic tomography with combined virtually parallel projecting and spatially adaptive filtering

An iterative sparse-view PAT reconstruction scheme is presented, where a concept of virtual parallel-projection matching the measurement condition is introduced to aid the “compressive sensing” in the reconstruction procedure, and meanwhile, the non-local spatially adaptive filtering exploring the a priori information of the mutual similarities in natural images is adopted to recover the unknowns in the transformed sparse domain.

Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering

An iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the “compressive sensing” procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduction to effectively recover the partial unknown coefficients in the transformed domain.

Deep learning optoacoustic tomography with sparse data

A new framework for efficient recovery of image quality from sparse optoacoustic data based on a deep convolutional neural network is proposed and its performance with whole body mouse imaging in vivo is demonstrated.

Sub-sampled Fabry-Perot photoacoustic scanner for fast 3D imaging

The planar Fabry Perot (FP) photoacoustic scanner provides exquisite high resolution 3D images of soft tissue structures for sub-cm penetration depths. However, as the FP sensor is optically



Full-view photoacoustic tomography using asymmetric distributed sensors optimized with compressed sensing method

The Application of Compressed Sensing for Photo-Acoustic Tomography

This paper suggests a new reconstruction strategy using the compressed sensing formalism which states that a small number of linear projections of a compressible image contain enough information for reconstruction to dramatically reduce the number of measurements needed for a given quality of reconstruction.

In vivo optical-resolution photoacoustic computed tomography with compressed sensing.

Compared with conventional backprojection reconstruction, the CS-PKS strategy was shown to produce high-quality in vivo OR-PACT images with threefold less measurement data, which can be leveraged to improve the data acquisition speed and costs of OR- PACT systems.

Full-Wave Iterative Image Reconstruction in Photoacoustic Tomography With Acoustically Inhomogeneous Media

A discrete imaging model for PACT is developed that is based on the exact photoacoustic (PA) wave equation and facilitates the circumvention of these limitations and permits application of a wide-range of modern image reconstruction algorithms that can mitigate the effects of data incompleteness and noise.

On the adjoint operator in photoacoustic tomography

Photoacoustic tomography (PAT) is an emerging biomedical imaging from coupled physics technique, in which the image contrast is due to optical absorption, but the information is carried to the

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A completely new acquisition and reconstruction scheme is reported to achieve artefact-free imaging from limited-view acquisition to potentially eliminate both the mechanical scanning of single-element ultrasonic transducer and the expensive ultrasonic array transducers.

Multiscale photoacoustic microscopy and computed tomography.

PAT holds the promise of in vivo imaging at multiple length scales ranging from subcellular organelles to organs with the same contrast origin, an important application in multiscale systems biology research.

Optoacoustic Imaging and Tomography: Reconstruction Approaches and Outstanding Challenges in Image Performance and Quantification

The currently available optoacoustic image reconstruction and quantification approaches are assessed, including back-projection and model-based inversion algorithms, sparse signal representation, wavelet-based approaches, methods for reduction of acoustic artifacts as well as multi-spectral methods for visualization of tissue bio-markers.

Patterned interrogation scheme for compressed sensing photoacoustic imaging using a Fabry Perot planar sensor

An experimental implementation will be described, which employs a wide NIR tunable laser beam to interrogate the FPI sensor with patterned and compressed sensing for ultrasound detection, and a scrambled Hadamard operator is used in the experiments.

Acoustic Wave Field Reconstruction From Compressed Measurements With Application in Photoacoustic Tomography

A modification of the Curvelet frame is proposed to account for the smoothing effects of data acquisition and motivated by a frequency domain model for photoacoustic tomography.