Photoacoustic tomography and sensing in biomedicine

Photoacoustics has been broadly studied in biomedicine, for both human and small animal tissues. Photoacoustics uniquely combines the absorption contrast of light or radio frequency waves with ultrasound resolution. Moreover, it is non-ionizing and non-invasive, and is the fastest growing new biomedical method, with clinical applications on the way. This review provides a brief recap of recent developments in photoacoustics in biomedicine, from basic principles to applications. The emphasized areas include the new imaging modalities, hybrid detection methods, photoacoustic contrast agents and the photoacoustic Doppler effect, as well as translational research topics

Photoacoustic tomography of the mouse cerebral cortex with a high-numerical-aperture-based virtual point detector

The mouse cerebral cortex was imaged in situ by photoacoustic tomography (PAT). Instead of a flat ultrasonic transducer, a virtual point detector based on a high numerical aperture (NA), positively focused transducer was used. This virtual point detector has a wide omnidirectional acceptance angle, a high sensitivity, and a negligible aperture effect. In addition, the virtual point detector can be located much more closely to the object during the detection. Compared with a finite-size flat transducer, images generated by using this virtual point detector have both uniform signal-to-noise ratio (SNR) and resolution

A new framework of human interaction recognition based on multiple stage probability fusion

Visual-based human interactive behavior recognition is a challenging research topic in computer vision. There exist some important problems in the current interaction recognition algorithms, such as very complex feature representation and inaccurate feature extraction induced by wrong human body segmentation. In order to solve these problems, a novel human interaction recognition method based on multiple stage probability fusion is proposed in this paper. According to the human body’s contact in interaction as a cut-off point, the process of the interaction can be divided into three stages: start stage, execution stage and end stage. Two persons’ motions are respectively extracted and recognizes in the start stage and the finish stage when there is no contact between those persons. The two persons’ motion is extracted as a whole and recognized in the execution stage. In the recognition process, the final recognition results are obtained by the weighted fusing these probabilities in different stages. The proposed method not only simplifies the extraction and representation of features, but also avoids the wrong feature extraction caused by occlusion. Experiment results on the UT-interaction dataset demonstrated that the proposed method results in a better performance than other recent interaction recognition methods

A new framework of human interaction recognition based on multiple stage probability fusion

Visual-based human interactive behavior recognition is a challenging research topic in computer vision. There exist some important problems in the current interaction recognition algorithms, such as very complex feature representation and inaccurate feature extraction induced by wrong human body segmentation. In order to solve these problems, a novel human interaction recognition method based on multiple stage probability fusion is proposed in this paper. According to the human body’s contact in interaction as a cut-off point, the process of the interaction can be divided into three stages: start stage, execution stage and end stage. Two persons’ motions are respectively extracted and recognizes in the start stage and the finish stage when there is no contact between those persons. The two persons’ motion is extracted as a whole and recognized in the execution stage. In the recognition process, the final recognition results are obtained by the weighted fusing these probabilities in different stages. The proposed method not only simplifies the extraction and representation of features, but also avoids the wrong feature extraction caused by occlusion. Experiment results on the UT-interaction dataset demonstrated that the proposed method results in a better performance than other recent interaction recognition methods

Improving the image quality of photoacoustic tomography (PAT) by using a negative acoustic lens

Although a small point ultrasound transducer has a wide acceptance angle, its signal-to-noise (SNR) is low due to the high thermal-noise-induced electric voltages in the transducer, which is a result of its small active area. By contrast, a finite size flat transducer has high sensitivity (good SNR), but the acceptance angle is generally small, which limits its application in reconstruction-based photoacoustic tomography (PAT). In this paper, we report a negative lens concept to increase the acceptance angle for a flat transducer. We also provide phantom experiments that demonstrate this concept can greatly increase the detection region for PAT and without losing sensitivity

Fast and Robust Deconvolution-Based Image Reconstruction for Photoacoustic Tomography in Circular Geometry: Experimental Validation

Photoacoustic tomography (PAT) is a fast-developing biomedical imaging technology suitable for in vivo imaging. PAT in spherical or circular geometry gives good image resolution yet is slow or expensive in signal acquisition and image formation. Reducing the number of detection angles can ameliorate such issues, usually at the expense of image quality. This paper introduces a deconvolution-based algorithm that models the imaging process as a linear and shift-invariant system. As demonstrated by the in vivo experiment, this algorithm not only runs much faster than the back-projection algorithm but also shows stronger robustness in that it provides better image quality when detection angles are sparse. Therefore, this algorithm promises to enable real-time PAT in circular geometry

Negative lens concept for photoacoustic tomography

Although a small point ultrasound transducer has a wide acceptance angle, its small active area leads to a high thermal-noise-induced electric voltage in the transducer, thus the sensitivity is low. By contrast, a finite-size flat transducer has high sensitivity, but the acceptance angle is small, which limits its application in reconstruction-based photoacoustic tomography (PAT). Here, we propose a negative lens concept to increase the acceptance angle of a flat transducer without losing sensitivity. Phantom experiments demonstrate that use of this concept greatly increases the detection region for PAT with high sensitivity