eprintid: 10065248 rev_number: 23 eprint_status: archive userid: 608 dir: disk0/10/06/52/48 datestamp: 2019-01-08 12:05:30 lastmod: 2021-10-13 22:54:23 status_changed: 2019-01-08 12:05:30 type: article metadata_visibility: show creators_name: Lucka, F creators_name: Nam, H creators_name: Betcke, M creators_name: Zhang, E creators_name: Beards, P creators_name: Cox, B creators_name: Arridge, S title: Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 divisions: F42 keywords: photoacoustic tomography, dynamic imaging, compressed sensing, simultaneous motion estimation, variational regularization note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: 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 subsampled 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 2D numerical phantom will be used to illustrate the main properties of this recently developed joint-image-reconstructionand-motion-estimation framework, measured data from a dynamic experimental phantom will also be used to demonstrate its potential for challenging, large-scale, real-world, 3D 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. date: 2018 date_type: published publisher: SIAM PUBLICATIONS official_url: https://doi.org/10.1137/18M1170066 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green article_type_text: Article verified: verified_manual elements_id: 1535626 doi: 10.1137/18M1170066 language_elements: English lyricists_name: Arridge, Simon lyricists_name: Beard, Paul lyricists_name: Betcke, Marta lyricists_name: Cox, Benjamin lyricists_name: Huynh, Nam lyricists_name: Lucka, Felix lyricists_name: Zhang, Edward lyricists_id: SRARR14 lyricists_id: PCBEA63 lyricists_id: MMBET00 lyricists_id: BTCOX21 lyricists_id: NTHUY05 lyricists_id: FLUCK81 lyricists_id: EZZHA53 actors_name: Lucka, Felix actors_id: FLUCK81 actors_role: owner full_text_status: public publication: SIAM Journal on Imaging Sciences volume: 11 number: 4 pagerange: 2224-2253 pages: 30 issn: 1936-4954 citation: Lucka, F; Nam, H; Betcke, M; Zhang, E; Beards, P; Cox, B; Arridge, S; (2018) Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation. SIAM Journal on Imaging Sciences , 11 (4) pp. 2224-2253. 10.1137/18M1170066 <https://doi.org/10.1137/18M1170066>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10065248/1/1802.05184v3.pdf