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Non‐local means improves total‐variation constrained photoacoustic image reconstruction
Author(s) -
Yalavarthy Phaneendra K.,
Kalva Sandeep Kumar,
Pramanik Manojit,
Prakash Jaya
Publication year - 2021
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.202000191
Subject(s) - photoacoustic imaging in biomedicine , iterative reconstruction , computer science , noise reduction , total variation denoising , photoacoustic tomography , inversion (geology) , tomography , computer vision , algorithm , artificial intelligence , optics , physics , geology , paleontology , structural basin
Photoacoustic/Optoacoustic tomography aims to reconstruct maps of the initial pressure rise induced by the absorption of light pulses in tissue. This reconstruction is an ill‐conditioned and under‐determined problem, when the data acquisition protocol involves limited detection positions. The aim of the work is to develop an inversion method which integrates denoising procedure within the iterative model‐based reconstruction to improve quantitative performance of optoacoustic imaging. Among the model‐based schemes, total‐variation (TV) constrained reconstruction scheme is a popular approach. In this work, a two‐step approach was proposed for improving the TV constrained optoacoustic inversion by adding a non‐local means based filtering step within each TV iteration. Compared to TV‐based reconstruction, inclusion of this non‐local means step resulted in signal‐to‐noise ratio improvement of 2.5 dB in the reconstructed optoacoustic images.