Multiview spatial compounding using lens-based photoacoustic imaging system

Francis Kalloor Joseph, Chinni Bhargava, Sumohana Channappayya, Pachamuthu Rajalakshmi, Vikram S. Dogra, Navalgund Rao*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)
82 Downloads (Pure)

Abstract

Recently, an acoustic lens has been proposed for volumetric focusing as an alternative to conventional reconstruction algorithms in Photoacoustic (PA) Imaging. Acoustic lens can significantly reduce computational complexity and facilitate the implementation of real-time and cost-effective systems. However, due to the fixed focal length of the lens, the Point Spread Function (PSF) of the imaging system varies spatially. Furthermore, the PSF is asymmetric, with the lateral resolution being lower than the axial resolution. For many medical applications, such as in vivo thyroid, breast and small animal imaging, multiple views of the target tissue at varying angles are possible. This can be exploited to reduce the asymmetry and spatial variation of system the PSF with simple spatial compounding. In this article, we present a formulation and experimental evaluation of this technique. PSF improvement in terms of resolution and Signal to Noise Ratio (SNR) with the proposed spatial compounding is evaluated through simulation. Overall image quality improvement is demonstrated with experiments on phantom and ex vivo tissue. When multiple views are not possible, an alternative residual refocusing algorithm is proposed. The performances of these two methods, both separately and in conjunction, are compared and their practical implications are discussed.
Original languageEnglish
Pages (from-to)85-94
Number of pages10
JournalPhotoacoustics
Volume13
Early online date18 Feb 2019
DOIs
Publication statusPublished - 1 Mar 2019
Externally publishedYes

Keywords

  • UT-Hybrid-D
  • photoacoustic imaging
  • spatial compounding
  • Acoustic lens
  • Photoacoustic camera
  • Refocusing
  • Spatial compounding
  • Point Spread Function
  • Resolution

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