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

@article{Boink2018AFF, title={A framework for directional and higher-order reconstruction in photoacoustic tomography.}, author={Yoeri E. Boink and Marinus J. Lagerwerf and Wiendelt Steenbergen and Stephan A van Gils and Srirang Manohar and Christoph Brune}, journal={Physics in medicine and biology}, year={2018}, volume={63 4}, pages={ 045018 } }

Photoacoustic tomography is a hybrid imaging technique that combines high optical tissue contrast with high ultrasound resolution. Direct reconstruction methods such as filtered back-projection, time reversal and least squares suffer from curved line artefacts and blurring, especially in the case of limited angles or strong noise. In recent years, there has been great interest in regularised iterative methods. These methods employ prior knowledge of the image to provide higher quality…

## Figures from this paper

## 20 Citations

Model based image recovery in photoacoustic tomography using hybrid non-convex regularization.

- Mathematics, Computer Science
- 2019

We propose a novel model based image reconstruction method in photoacoustic tomography (PAT) involving a novel form of regularization that is specifically tuned for PAT images, and a novel…

Photo-acoustic tomographic image reconstruction from reduced data using physically inspired regularization

- MathematicsJournal of Instrumentation
- 2020

A model-based image reconstruction method for photoacoustic tomography involving a novel form of regularization including a modification of the form proposed for fluorescence image restoration is proposed and its ability to recover good quality images from significantly reduced size datasets is demonstrated.

A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation

- Computer ScienceIEEE Transactions on Medical Imaging
- 2020

This article proposes to jointly acquire the photoacoustic reconstruction and segmentation, by modifying a recently developed partially learned algorithm based on a convolutional neural network that enables higher quality reconstructions and segmentations than the state-of-the-art learned and non-learned methods.

TGV-regularized inversion of the Radon transform for photoacoustic tomography

- MathematicsBiomedical optics express
- 2020

The proposed TGV-regularized Radon inversion is a variational method that is shown to be capable of such artifact-free inversion and validated by numerical simulations, compared to filtered back projection (FBP), and performance-tested on real data from phantom as well as in-vivo mouse experiments.

Robustness of a partially learned photoacoustic reconstruction algorithm

- MathematicsBiOS
- 2019

This work investigates the stability of algorithms in which it combines the structure of model-based algorithms with the efficiency of data-driven neural networks, while maintaining the primal-dual structure and the information from the photoacoustic operator.

Real-time photoacoustic projection imaging using deep learning

- Computer Science
- 2018

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.

Photoacoustic imaging reconstruction using combined nonlocal patch and total-variation regularization for straight-line scanning

- MathematicsBiomedical engineering online
- 2018

Simulation and experiment results indicate that the patch-TV algorithm successfully solves the problems of PAI reconstruction and is highly effective in practical PAI applications.

Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation

- MathematicsSIAM J. Imaging Sci.
- 2018

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.

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

- MathematicsIEEE Transactions on Medical Imaging
- 2018

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.

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

- MathematicsMLMIR@MICCAI
- 2018

A framework for accelerated iterative reconstructions using a fast and approximate forward model that is based on k-space methods for photoacoustic tomography, which is able to produce superior results to total variation reconstructions with a speed-up of 32 times.

## References

SHOWING 1-10 OF 63 REFERENCES

Accelerated high-resolution photoacoustic tomography via compressed sensing.

- MathematicsPhysics in medicine and biology
- 2016

The results show that images with good spatial resolution and contrast can be obtained from highly sub-sampled PAT data if variational image reconstruction techniques that describe the tissues structures with suitable sparsity-constraints are used.

On the Adjoint Operator in Photoacoustic Tomography

- Mathematics
- 2016

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…

Higher-Order TV Methods—Enhancement via Bregman Iteration

- MathematicsJ. Sci. Comput.
- 2013

This work analyzes and compares two recent variational models for image denoising and improves their reconstructions by applying a Bregman iteration strategy and discusses efficient numerical realizations of BRegman iterations and modified versions thereof.

Compressed sensing and sparsity in photoacoustic tomography

- Mathematics
- 2016

This work demonstrates, that the number of measurements can significantly be reduced by allowing general linear measurements instead of point-wise pressure values, and develops the concept of sparsifying temporal transforms for three-dimensional photoacoustic tomography.

Total variation based gradient descent algorithm for sparse-view photoacoustic image reconstruction.

- Computer ScienceUltrasonics
- 2012

The Application of Compressed Sensing for Photo-Acoustic Tomography

- PhysicsIEEE Transactions on Medical Imaging
- 2009

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.

Sparse-view x-ray CT reconstruction via total generalized variation regularization.

- Computer SciencePhysics in medicine and biology
- 2014

Experimental results show that the present PWLS-TGV method can achieve images with several noticeable gains over the original TV-based method in terms of accuracy and resolution properties.

Exact and approximative imaging methods for photoacoustic tomography using an arbitrary detection surface.

- Physics, MathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
- 2007

Two universal reconstruction methods for photoacoustic computed tomography are derived, applicable to an arbitrarily shaped detection surface, by calculating the far-field approximation, a concept well known in physics, where the generated acoustic wave is approximated by an outgoing spherical wave with the reconstruction point as center.

Generalized total variation iterative constraint strategy in limited angle optical diffraction tomography.

- PhysicsOptics express
- 2016

A new two-stage regularization strategy, named Generalized Total Variation Iterative Constraint (GTVIC), dedicated to semi-piecewise-constant objects, successfully applied as a supplementary module for two different reconstruction algorithms: an X-ray type solver and a diffraction-wise solver.

Image reconstruction in a passive element enriched photoacoustic tomography setup

- Physics
- 2010

Photoacoustic imaging is a relatively new imaging technology, in which an object is illuminated with optical energy and where in return measurements are taken in the acoustical domain, in order to…