scholarly journals Dual-Polarized Fiber Laser Sensor for Photoacoustic Microscopy

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4632 ◽  
Author(s):  
Lin ◽  
Liang ◽  
Jin ◽  
Wang
Keyword(s):  
Fiber Laser ◽  
Optical Resolution ◽  
High Sensitivity ◽  
Low Noise ◽  
Laser Sensor ◽  
Photoacoustic Microscopy ◽  
Label Free ◽  
Laser Sensors ◽  
Dual Polarized

Optical resolution photoacoustic microscopy (OR-PAM) provides high-resolution, label-free and non-invasive functional imaging for broad biomedical applications. Dual-polarized fiber laser sensors have high sensitivity, low noise, a miniature size, and excellent stability; thus, they have been used in acoustic detection in OR-PAM. Here, we review recent progress in fiber-laser-based ultrasound sensors for photoacoustic microscopy, especially the dual-polarized fiber laser sensor with high sensitivity. The principle, characterization and sensitivity optimization of this type of sensor are presented. In vivo experiments demonstrate its excellent performance in the detection of photoacoustic (PA) signals in OR-PAM. This review summarizes representative applications of fiber laser sensors in OR-PAM and discusses their further improvements.

scholarly journals High-Sensitivity Optical-Resolution Photoacoustic Microscopy with an Optical-Acoustic Combiner Based on an Off-Axis Parabolic Acoustic Mirror

Photonics ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 127
Author(s):  
Xiang Zhang ◽  
Yang Liu ◽  
Chao Tao ◽  
Jie Yin ◽  
Zizhong Hu ◽  
...  
Keyword(s):  
Optical Resolution ◽  
High Sensitivity ◽  
Detection Sensitivity ◽  
Good Resolution ◽  
Photoacoustic Microscopy ◽  
Label Free ◽  
High Quality ◽  
In Vivo Experiments ◽  
Acoustic Focusing

Optical-resolution photoacoustic microscopy (OR-PAM) is a promising noninvasive biomedical imaging technology with label-free optical absorption contrasts. Performance of OR-PAM is usually closely related to the optical-acoustic combiner. In this study, we propose an optical-acoustic combiner based on a flat acoustic reflector and an off-axis parabolic acoustic mirror with a conical bore. Quantitative simulation and experiments demonstrated that this combiner can provide better acoustic focusing performance and detection sensitivity. Moreover, OR-PAM is based on the combiner suffer low optical disorders, which guarantees the good resolution. In vivo experiments of the mouse brain and the iris were also conducted to show the practicability of the combiner in biomedicine. This proposed optical-acoustic combiner realizes a high-quality optical-acoustic confocal alignment with minimal optical disorders and acoustic insertion loss, strong acoustic focusing, and easy implementation. These characteristics might be useful for improving the performance of OR-PAM.

scholarly journals In vivo near-realtime volumetric optical-resolution photoacoustic microscopy using a high-repetition-rate nanosecond fiber-laser

2011 ◽  
Vol 19 (18) ◽  
pp. 17143 ◽  
Author(s):  
Wei Shi ◽  
Parsin Hajireza ◽  
Peng Shao ◽  
Alexander Forbrich ◽  
Roger J. Zemp
Keyword(s):  
Fiber Laser ◽  
Repetition Rate ◽  
Optical Resolution ◽  
High Repetition Rate ◽  
Photoacoustic Microscopy ◽  
High Repetition

Label-free in vivo fiber-based optical-resolution photoacoustic microscopy

2011 ◽  
Vol 36 (20) ◽  
pp. 4107 ◽  
Author(s):  
P. Hajireza ◽  
W. Shi ◽  
R. J. Zemp
Keyword(s):  
Optical Resolution ◽  
Photoacoustic Microscopy ◽  
Label Free

scholarly journals Recovery of photoacoustic images based on accurate ultrasound positioning

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yinhao Pan ◽  
Ningbo Chen ◽  
Liangjian Liu ◽  
Chengbo Liu ◽  
Zhiqiang Xu ◽  
...  
Keyword(s):  
Biological Tissue ◽  
Large Field ◽  
Photoacoustic Microscopy ◽  
Label Free ◽  
Imaging Data ◽  
Motor Speed ◽  
Image Correction ◽  
Microscopy Imaging ◽  
Scanning Method

AbstractPhotoacoustic microscopy is an in vivo imaging technology based on the photoacoustic effect. It is widely used in various biomedical studies because it can provide high-resolution images while being label-free, safe, and harmless to biological tissue. Polygon-scanning is an effective scanning method in photoacoustic microscopy that can realize fast imaging of biological tissue with a large field of view. However, in polygon-scanning, fluctuations of the rotating motor speed and the geometric error of the rotating mirror cause image distortions, which seriously affect the photoacoustic-microscopy imaging quality. To improve the image quality of photoacoustic microscopy using polygon-scanning, an image correction method is proposed based on accurate ultrasound positioning. In this method, the photoacoustic and ultrasound imaging data of the sample are simultaneously obtained, and the angle information of each mirror used in the polygon-scanning is extracted from the ultrasonic data to correct the photoacoustic images. Experimental results show that the proposed method can significantly reduce image distortions in photoacoustic microscopy, with the image dislocation offset decreasing from 24.774 to 10.365 μm.

scholarly journals Subwavelength-resolution label-free photoacoustic microscopy of optical absorption in vivo

2010 ◽  
Vol 35 (19) ◽  
pp. 3195 ◽  
Author(s):  
Chi Zhang ◽  
Konstantin Maslov ◽  
Lihong V. Wang
Keyword(s):  
Optical Absorption ◽  
Photoacoustic Microscopy ◽  
Label Free ◽  
Subwavelength Resolution

scholarly journals Deep-learning-based motion-correction algorithm in optical resolution photoacoustic microscopy

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Xingxing Chen ◽  
Weizhi Qi ◽  
Lei Xi
Keyword(s):  
Deep Learning ◽  
Optical Resolution ◽  
Motion Artifacts ◽  
Photoacoustic Microscopy ◽  
Simulation Studies ◽  
Correction Algorithm ◽  
Brain Vessels ◽  
Capillary Networks ◽  
Motion Corrections

Abstract In this study, we propose a deep-learning-based method to correct motion artifacts in optical resolution photoacoustic microscopy (OR-PAM). The method is a convolutional neural network that establishes an end-to-end map from input raw data with motion artifacts to output corrected images. First, we performed simulation studies to evaluate the feasibility and effectiveness of the proposed method. Second, we employed this method to process images of rat brain vessels with multiple motion artifacts to evaluate its performance for in vivo applications. The results demonstrate that this method works well for both large blood vessels and capillary networks. In comparison with traditional methods, the proposed method in this study can be easily modified to satisfy different scenarios of motion corrections in OR-PAM by revising the training sets.

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