activity
20162022
most citedModel based learning for accelerated, limited-view 3D photoacoustic tomography

347 citations · 426 across the 6 of their papers we have counts for

collaborators

8 papers

physics.med-ph2022★ 29 cited

Ultrathin, high-speed, all-optical photoacoustic endomicroscopy probe for guiding minimally invasive surgery

Tianrui Zhao, Truc Thuy Pham, Christian Baker +6

Photoacoustic (PA) endoscopy has shown significant potential for clinical diagnosis and surgical guidance. Multimode fibres (MMFs) are becoming increasing attractive for the develo…

cs.CV2020★ 1 cited

Photoacoustic Reconstruction Using Sparsity in Curvelet Frame: Image versus Data Domain

Bolin Pan, Simon R. Arridge, Felix Lucka +5

Curvelet frame is of special significance for photoacoustic tomography (PAT) due to its sparsifying and microlocalisation properties. We derive a one-to-one map between wavefront d…

physics.optics2020

Single-shot hybrid photoacoustic-fluorescent microendoscopy through a multi-mode fiber with wavefront shaping

Sylvain Mezil, Antonio M. Caravaca-Aguirre, Edward Z. Zhang +4

We present a minimally-invasive endoscope based on a multimode fiber that combines photoacoustic and fluorescence sensing. From the measurement of a transmission matrix during a pr…

cs.CV2018★ 15 cited

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

Andreas Hauptmann, Ben Cox, Felix Lucka +4

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 appro…

math.NA2018★ 34 cited

Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation

Felix Lucka, Nam Huynh, Marta Betcke +4

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 demon…

cs.CV2017★ 347 cited

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

Andreas Hauptmann, Felix Lucka, Marta Betcke +6

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…

math.NA2016

Acoustic Wave Field Reconstruction from Compressed Measurements with Application in Photoacoustic Tomography

Marta M. Betcke, Ben T. Cox, Nam Huynh +3

We present a method for the recovery of compressively sensed acoustic fields using patterned, instead of point-by-point, detection. From a limited number of such compressed measure…

math.PR2016

Nonzero-sum stochastic differential games with impulse controls: a verification theorem with applications

René Aïd, Matteo Basei, Giorgia Callegaro +2

We consider a general nonzero-sum impulse game with two players. The main mathematical contribution of the paper is a verification theorem which provides, under some regularity con…