期刊
JOURNAL OF BIOMEDICAL OPTICS
卷 22, 期 11, 页码 -出版社
SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.JBO.22.11.116001
关键词
photoacoustic data; deep neural network; bandwidth enhancement; reconstruction
资金
- Department of Biotechnology (DBT) Innovative Young Biotechnologist Award (IYBA) [BT/07/IYBA/2013-13]
- DBT Bioengineering Grant [BT/PR7994/MED/32/284/2013]
- Tier 1 grant - Ministry of Education in Singapore [RG41/14: M4011285, RG48/16: M4011617]
- Singapore National Research Foundation [NMRC/OFIRG/0005/2016: M4062012]
Photoacoustic (PA) signals collected at the boundary of tissue are always band-limited. A deep neural network was proposed to enhance the bandwidth (BW) of the detected PA signal, thereby improving the quantitative accuracy of the reconstructed PA images. A least square-based deconvolution method that utilizes the Tikhonov regularization framework was used for comparison with the proposed network. The proposed method was evaluated using both numerical and experimental data. The results indicate that the proposed method was capable of enhancing the BW of the detected PA signal, which inturn improves the contrast recovery and quality of reconstructed PA images without adding any significant computational burden.(C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
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