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Titel:

Deep learning methods hold promise for light fluence compensation in three-dimensional optoacoustic imaging

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Madasamy, Arumugaraj; Gujrati, Vipul; Ntziachristos, Vasilis; Prakash, Jaya
Abstract:
Significance: Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect. Aim: Different DL models were comp...     »
Zeitschriftentitel:
Journal of Biomedical Optics
Zeitschriftentitel:
J Biomed Opt
Jahr:
2022
Band / Volume:
27
Heft / Issue:
10
Volltext / DOI:
doi:10.1117/1.JBO.27.10.106004
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/36209354
WWW:
https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-27/issue-10/106004/Deep-learning-methods-hold-promise-for-light-fluence-compensation-in/10.1117/1.JBO.27.10.106004.full
Print-ISSN:
1083-3668
TUM Einrichtung:
Lehrstuhl für Biologische Bildgebung - Zusammenarbeit mit dem Helmholtz-Zentrum München (Prof. Ntziachristos)
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