Sparse recovery algorithms have shown great potential to reconstruct images with limited view datasets in optoacoustic tomography, with a disadvantage of being computational expensive. In this paper, we improve the fast convergent Split Augmented Lagrangian Shrinkage Algorithm (SALSA) method based on least square QR (LSQR) formulation for performing accelerated reconstructions. Further, coherence factor is calculated to weight the final reconstruction result, which can further reduce artifacts arising in limited-view scenarios and acoustically heterogeneous mediums. Several phantom and biological experiments indicate that the accelerated SALSA method with coherence factor (ASALSA-CF) can provide improved reconstructions and much faster convergence compared to existing sparse recovery methods.
A hybrid optical and acoustic resolution optoacoustic endoscopy is proposed. Laser light is transmitted to tissue by two types of illumination for optical and acoustic resolution imaging respectively. An unfocused ultrasound detector is used for recording optoacoustic signals. The endoscopy probe attains 3.6 mm diameter and is fully encapsulated into a catheter system. We examine the performance of the hybrid endoscope with phantoms and tissue sample, which shows that the hybrid endoscopy can obtain optical resolution in superficial microscopic imaging and ultrasonic tomography reconstruction resolution when imaging at greater depths.
In optoacoustic imaging, the resolution and image quality in a certain imaging position usually cannot be enhanced without changing the imaging configuration. Post-reconstruction image processing methods offer a new possibility to improve image quality and resolution. We have developed a geometrical super-resolution (GSR) method which uses information from spatially separated frames to enhance resolution and contrast in optoacoustic images. The proposed method acquires several low resolution images from the same object located at different positions inside the imaging plane. Thereafter, it applies an iterative registration algorithm to integrate the information in the acquired set of images to generate a single high resolution image. Herein, we present the method and evaluate its performance in simulation and phantom experiments, and results show that geometrical super-resolution techniques can be a promising alternative to enhance resolution in optoacoustic imaging.
Optoacoustic technique has been shown to resolve anatomical, functional and molecular features at depths that go beyond the reach of epi-illumination optical microscopy offering new opportunities for endoscopic imaging. Herein, we interrogate the merits of optoacoustic endoscopy implemented by translating a sound detector in linear or curved geometries. The linear and curved detection geometries are achieved by employing an intravascular ultrasound transducer (IVUS) within a plastic guide shaped to a line or a curve. This concept could be used together with optical endoscopes to yield hybrid optical and optoacoustic imaging.