Deep learning acceleration of iterative model-based light fluence correction for photoacoustic tomography

Photoacoustic tomography (PAT) is a promising imaging technique that can visualize the distribution of chromophores within biological tissue. However, the accuracy of PAT imaging is compromised by light fluence (LF), which hinders the quantification of light absorbers. Currently, model-based iterati...

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Bibliografiske detaljer

Principais autores:	Zhaoyong Liang, Shuangyang Zhang, Zhichao Liang, Zongxin Mo, Xiaoming Zhang, Yutian Zhong, Wufan Chen, Li Qi
Format:	Artigo
Sprog:	Inglês
Udgivet:	Elsevier 2024-06-01
Serier:	Photoacoustics
Fag:	Photoacoustic tomography Iterative light fluence correction Fourier neural operator Operator learning
Online adgang:	http://www.sciencedirect.com/science/article/pii/S2213597924000181
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