Distributed compressed sensing for photo-acoustic imaging

K. J. Francis, P. Rajalakshmi, Sumohana S. Channappayya

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)


Photo-Acoustic Tomography (PAT) combines ultrasound resolution and penetration with endogenous optical contrast of tissue. Real-time PAT imaging is limited by the number of parallel data acquisition channels and pulse repetition rate of the laser. Typical photoacoustic signals afford sparse representation. Additionally, PAT transducer configurations exhibit significant intra- and inter- signal correlation. In this work, we formulate photoacoustic signal recovery in the Distributed Compressed Sensing (DCS) framework to exploit this correlation. Reconstruction using the proposed method achieves better image quality than compressed sensing with significantly fewer samples. Through our results, we demonstrate that DCS has the potential to achieve real-time PAT imaging.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Number of pages5
ISBN (Electronic)9781479983391
Publication statusPublished - 9 Dec 2015
Externally publishedYes
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 27 Sept 201530 Sept 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


ConferenceIEEE International Conference on Image Processing, ICIP 2015
Abbreviated titleICIP
CityQuebec City


  • Distributed Compressive Sensing
  • Joint sparsity
  • Photo-Acoustic Tomography


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