Deep neural network-based bandwidth enhancement of photoacoustic data.

Journal: Journal of biomedical optics
Published Date:

Abstract

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.

Authors

  • Sreedevi Gutta
    Indian Institute of Science, Department of Computational and Data Sciences, Bangalore, Karnataka, India.
  • Venkata Suryanarayana Kadimesetty
    Indian Institute of Science, Department of Computational and Data Sciences, Bangalore, Karnataka, India.
  • Sandeep Kumar Kalva
    Nanyang Technological University, School of Chemical and Biomedical Engineering, Singapore.
  • Manojit Pramanik
    School of Chemical and Biomedical Engineering, Nanyang Technological University, 62 Nanyang Drive, Singapore, 637459 Singapore.
  • Sriram Ganapathy
    Indian Institute of Science, Bangalore, India.
  • Phaneendra K Yalavarthy
    Indian Institute of Science, Department of Computational and Data Sciences, Bangalore, Karnataka, India.