title: Improving Optoacoustic Image Quality via Geometric Pixel Super-Resolution Approach.
abstract: High fidelity optoacoustic (photoacoustic) tomography requires dense spatial sampling of optoacoustic signals using point acoustic detectors. However, in practice, spatial resolution of the images is often limited by limited sampling either due to coarse multi-element arrays or time in raster scan measurements. Herein, we investigate a method that integrates information from multiple optoacoustic images acquired at sub-diffraction steps into one high resolution image by means of an iterative registration algorithm. Experimental validations performed in target phantoms and ex vivo tissue samples confirm that the suggested approach renders significant improvements in terms of optoacoustic image resolution and quality without introducing significant alterations into the signal acquisition hardware or inversion algorithms.
authors.forename: Hailong
authors.initials: H
authors.lastname: He
authors.forename: Subhamoy
authors.initials: S
authors.lastname: Mandal
authors.forename: Andreas
authors.initials: A
authors.lastname: Buehler
authors.forename: X  Luís
authors.initials: X
authors.lastname: Deán-Ben
authors.forename: Daniel
authors.initials: D
authors.lastname: Razansky
authors.forename: Vasilis
authors.initials: V
authors.lastname: Ntziachristos
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004867:Equipment Design; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007668:Kidney / Q000000981:diagnostic imaging; D051379:Mice; D019047:Phantoms, Imaging; D061088:Photoacoustic Techniques / Q000379:methods*