The lensless endoscope is a promising device designed to image tissues in vivo at the cellular scale. The traditional acquisition setup consists in raster scanning during which the focused light beam from the optical fiber illuminates sequentially each pixel of the field of view (FOV). The calibration step to focus the beam and the sampling scheme both take time. In this preliminary work, we propose a scanning method based on compressive sampling theory. The method does not rely on a focused beam but rather on the random illumination patterns generated by the single-mode fibers. Experiments are performed on synthetic data for different compression rates (from 10 to 100% of the FOV)
Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging t...
We describe an imaging approach based on an optical setup made up of a miniature, lensless, minimall...
Minimally invasive medical procedures will benefit from flexible endoscopes that are extremely thin ...
Compressed sensing (CS) is a signal processing technique that provides a theoretical framework for a...
Project Report we present the development of diverse imaging systems based on Compressive Sensing or...
International audienceFluorescence imaging through ultrathin fibers is a promising approach to obtai...
Fiber-based endoscopic compressive imaging is a promising field for minimal invasive, in vivo imagin...
In this paper, a novel single-pixel method for coherent imaging through an endoscopic fiber bundle i...
An iterative algorithm is used to reconstruct the spectra of light passing through a scanning Michel...
In this paper a novel single-pixel method for coherent imaging through an endoscopic fiber bundle is...
Compressive imaging is an emerging field which allows one to acquire far fewer measurements of a sce...
Lensless endoscopy (LE) with multicore fibers (MCF) enables fluorescent imaging of biological sample...
In this study, we developed a signal processing method for fixed pattern noise removal in fiber-bund...
We propose and experimentally demonstrate a new concept of endo-microscopy: compressive multimode (M...
Endoscopy is a key technology for minimally-invasive optical access to deep tissues in humans and li...
Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging t...
We describe an imaging approach based on an optical setup made up of a miniature, lensless, minimall...
Minimally invasive medical procedures will benefit from flexible endoscopes that are extremely thin ...
Compressed sensing (CS) is a signal processing technique that provides a theoretical framework for a...
Project Report we present the development of diverse imaging systems based on Compressive Sensing or...
International audienceFluorescence imaging through ultrathin fibers is a promising approach to obtai...
Fiber-based endoscopic compressive imaging is a promising field for minimal invasive, in vivo imagin...
In this paper, a novel single-pixel method for coherent imaging through an endoscopic fiber bundle i...
An iterative algorithm is used to reconstruct the spectra of light passing through a scanning Michel...
In this paper a novel single-pixel method for coherent imaging through an endoscopic fiber bundle is...
Compressive imaging is an emerging field which allows one to acquire far fewer measurements of a sce...
Lensless endoscopy (LE) with multicore fibers (MCF) enables fluorescent imaging of biological sample...
In this study, we developed a signal processing method for fixed pattern noise removal in fiber-bund...
We propose and experimentally demonstrate a new concept of endo-microscopy: compressive multimode (M...
Endoscopy is a key technology for minimally-invasive optical access to deep tissues in humans and li...
Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging t...
We describe an imaging approach based on an optical setup made up of a miniature, lensless, minimall...
Minimally invasive medical procedures will benefit from flexible endoscopes that are extremely thin ...