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Deep neural network-based bandwidth enhancement of photoacoustic data

Gutta, Sreedevi and Kadimesetty, Venkata Suryanarayana and Kalva, Sandeep Kumar and Pramanik, Manojit and Ganapathy, Sriram and Yalavarthy, Phaneendra K (2017) Deep neural network-based bandwidth enhancement of photoacoustic data. In: JOURNAL OF BIOMEDICAL OPTICS, 22 (11).

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Official URL: http://dx.doi.org/10.1117/1.JBO.22.11.116001


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)

Item Type: Journal Article
Publisher: 10.1117/1.JBO.22.11.116001
Additional Information: Copy right for this article belongs to the SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS, 1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98225 USA
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Date Deposited: 13 Jan 2018 06:30
Last Modified: 13 Jan 2018 06:30
URI: http://eprints.iisc.ac.in/id/eprint/58599

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