The Application of Compressed Sensing for Photo-Acoustic Tomography

• Published in: IEEE transactions on medical imaging Vol. 28; no. 4; pp. 585 - 594
• Main Authors: Provost, J., Lesage, F.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Animals; Compressed sensing; compressive sampling; Computer Simulation; Costs; curvelets; High-resolution imaging; Image coding; Image Processing, Computer-Assisted - methods; Image reconstruction; Medical imaging; Optical imaging; Optical sensors; Optics and Photonics; Phantoms, Imaging; photoacoustic imaging; Reconstruction algorithms; Signal Processing, Computer-Assisted; Tomography; Tomography - methods; Transducers; Ultrasonics; wavelets
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2008.2007825

Photo-acoustic (PA) imaging has been developed for different purposes, but recently, the modality has gained interest with applications to small animal imaging. As a technique it is sensitive to endogenous optical contrast present in tissues and, contrary to diffuse optical imaging, it promises to bring high resolution imaging for in vivo studies at midrange depths (3-10 mm). Because of the limited amount of radiation tissues can be exposed to, existing reconstruction algorithms for circular tomography require a great number of measurements and averaging, implying long acquisition times. Time-resolved PA imaging is therefore possible only at the cost of complex and expensive electronics. This paper suggests a new reconstruction strategy using the compressed sensing formalism which states that a small number of linear projections of a compressible image contain enough information for reconstruction. By directly sampling the image to recover in a sparse representation, it is possible to dramatically reduce the number of measurements needed for a given quality of reconstruction.