Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/86305
Title: Deep neural network-based bandwidth enhancement of photoacoustic data
Authors: Gutta, Sreedevi
Kadimesetty, Venkata Suryanarayana
Kalva, Sandeep Kumar
Pramanik, Manojit
Ganapathy, Sriram
Yalavarthy, Phaneendra K.
Keywords: Photoacoustic data
Deep neural network
Issue Date: 2017
Source: Gutta, S., Kadimesetty, V. S., Kalva, S. K., Pramanik, M., Ganapathy, S., & Yalavarthy, P. K. (2017). Deep neural network-based bandwidth enhancement of photoacoustic data. Journal of Biomedical Optics, 22(11), 116001-.
Series/Report no.: Journal of Biomedical Optics
Abstract: Photoacoustic (PA) signals collected at the boundary of tissue are always band-limited. A deep neural network (DNN) was proposed to enhance the bandwidth 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 bandwidth of the detected PA signal, which inturn improves the contrast recovery and quality of reconstructed PA images without adding any significant computational burden.
URI: https://hdl.handle.net/10356/86305
http://hdl.handle.net/10220/43993
ISSN: 1083-3668
DOI: 10.1117/1.JBO.22.11.116001
Rights: © 2017 Society of Photo-optical Instrumentation Engineers (SPIE). This paper was published in Journal of Biomedical Optics and is made available as an electronic reprint (preprint) with permission of SPIE. The published version is available at: [http://dx.doi.org/10.1117/1.JBO.22.11.116001]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

Files in This Item:
File Description SizeFormat 
Deep neural network-based bandwidth enhancement of photoacoustic data.pdf2.41 MBAdobe PDFThumbnail
View/Open

SCOPUSTM   
Citations 20

10
Updated on Sep 4, 2020

PublonsTM
Citations 10

16
Updated on Mar 3, 2021

Page view(s)

264
Updated on Jun 14, 2021

Download(s) 20

246
Updated on Jun 14, 2021

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.