Model-based optoacoustic image reconstruction of large three-dimensional tomographic datasets acquired with an array of directional detectors

Miguel Angel Áraque Caballero, Jerome Gateau, Xose Luis Dean-Ben, Vasilis Ntziachristos

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Image quality in 3-D optoacoustic (photoacoustic) tomography is greatly influenced by both themeasurement system, in particular the number and spatial arrangement of ultrasound sensors, and the ability to account for the spatio-temporal response of the sensor element(s) in the reconstruction algorithm. Herein we present a reconstruction procedure based on the inversion of a time-domain forward model incorporating the spatial impulse response due to the shape of the transducer,which is subsequently applied in a tomographic system based on a translation-rotation scan of a linear detector array. The proposed method was also adapted to cope with the data-intensive requirements of high-resolution volumetric optoacoustic imaging. The processing of 2·104 individual signals resulted in well-resolved images of both ∼ 200 μm absorbers in phantoms and complex vascular structures in biological tissue. The results reported herein demonstrate that the introduced model-based methodology exhibits a better contrast and resolution than standard back-projection and model-based algorithms that assume point detectors. Moreover, the capability of handling large datasets anticipates that model-basedmethods incorporating the sensor properties can become standard practice in volumetric optoacoustic image formation.

Original languageEnglish
Article number6636031
Pages (from-to)433-443
Number of pages11
JournalIEEE Transactions on Medical Imaging
Volume33
Issue number2
DOIs
StatePublished - Feb 2014

Keywords

  • Computed tomography
  • inverse problems
  • opto acoustic
  • spatial impulse response

Fingerprint

Dive into the research topics of 'Model-based optoacoustic image reconstruction of large three-dimensional tomographic datasets acquired with an array of directional detectors'. Together they form a unique fingerprint.

Cite this