In recent years, photoacoustic imaging, as a new type of biomedical imaging method, combines the advantages of high selectivity in pure optical tissue imaging and deep penetration in pure ultrasound tissue imaging to obtain high-resolution and high-contrast tissue images. The use of photoacoustic imaging technology to deal with complex medical tissue problems is still a new research direction. How to compress large amounts of data and quickly transmit and store important value information has become a problem waiting for optimization. This paper uses the StagewiseOMP and tracking algorithm to combine it with the photoacoustic imaging of the k-wave simulation toolbox to rebuild a virtual simulation platform for blood vessel imaging. On the one hand, compressed sensing can reduce the sampling rate and speed up imaging. On the other hand, it can modify the demand for hardware equipment to facilitate data transmission and storage. A simulation model of photoacoustic field propagation, photoacoustic signal recording and image reconstruction was established using the k-wave simulation toolbox. We have used the excellent performance of the simulation platform through imaging technology to complete the imaging restoration of part of the blood area tube tissue.
As a new non-destructive biomedical imaging modality, photoacoustic imaging not only has high contrast of optical imaging but also has high penetration depth of ultrasonic imaging. And it has developed rapidly in recent years and has been widely used in the fields of biomedical clinical diagnosis and volume imaging, attracted the eager attention of more and more researchers in the biomedical field. In biomedicine, image reconstruction needs to process the huge amount of information obtained. How to compress the data without distortion in this process has become an important research topic. In this paper, based on photoacoustic imaging technology and compression sensing reconstruction algorithm, a virtual simulation platform for compression sensing photoacoustic tomography is constructed by using k-wave simulation toolbox. Through this platform, a simulation model of photoacoustic propagation was established, we analyzed the photoacoustic signal generated by the simulation model. Finally, image reconstruction is completed by using compression sensing reconstruction algorithm. Then, in order to test the performance of the platform, we reconstructed part of the blood vessel network image based on the simulation platform. The results show that the virtual simulation platform successfully realizes the compressed sensing photoacoustic tomography with small amount of data but high reconstruction quality, which has practical significance and theoretical value for the research of the application of compress sensing in photoacoustic imaging.
In recent years, photoacoustic imaging, an emerging nondestructive biomedical imaging technology, has shown great potential for early diagnosis of diseases with its advantages of highly sensitive optical contrast and high resolution. It is a hard project to collect a large number of pathological medical images by using photoacoustic imaging. How to compress large amounts of data, rapid transmission and storage of important value information has become an urgent problem to be solved. In this paper, build a virtual simulation platform for compressed sensing photoacoustic tomography by combining compressed sensing reconstruction algorithms with photoacoustic imaging based on the k-wave simulation toolbox. On the one hand, compressed sensing can reduce sample rates, accelerated the speed of imaging. On the other hand, it can modify the demands for hardware devices and facilitate to transmit and store of data. The k-wave simulation toolbox is used to build simulation models for simulating the propagation of photoacoustic fields, recording of photoacoustic signals, and image reconstruction. We validated the performance of the simulation platform by imaging the vascular network. The results show that the virtual simulation platform compressed sensing photoacoustic tomography can achieve high-quality photoacoustic imaging with less data. The virtual platform can provide theoretical guidance for the application of compressed sensing in photoacoustic imaging.
In recent years, photoacoustic imaging, an emerging nondestructive biomedical imaging technology, has shown great potential for early diagnosis of diseases with its advantages of highly sensitive optical contrast and high resolution. It is a hard project to collect a large number of pathological medical images by using photoacoustic imaging. How to compress large amounts of data, rapid transmission and storage of important value information has become an urgent problem to be solved. In this paper, build a virtual simulation platform for compressed sensing photoacoustic tomography by combining compressed sensing reconstruction algorithms with photoacoustic imaging based on the k-wave simulation toolbox. On the one hand, compressed sensing can reduce sample rates, accelerated the speed of imaging. On the other hand, it can modify the demands for hardware devices and facilitate to transmit and store of data. The k-wave simulation toolbox is used to build simulation models for simulating the propagation of photoacoustic fields, recording of photoacoustic signals, and image reconstruction. We validated the performance of the simulation platform by imaging the vascular network. The results show that the virtual simulation platform compressed sensing photoacoustic tomography can achieve high-quality photoacoustic imaging with less data. The virtual platform can provide theoretical guidance for the application of compressed sensing in photoacoustic imaging.
Ultrasonic transducer is a sensor that realizes the mutual conversion of ultrasonic and electrical signals, and it is widely used in quality inspection, biomedical imaging and other fields. Commonly used ultrasonic transducers have a small detection range and low sensitivity due to the diffraction of sound waves. Focused transducers are used to improve detection sensitivity. Unfortunately, focused transducers have narrow depth of field. Here, we developed a Bessel ultrasonic transducer for large depth of field by using conical acoustic lens. An acoustic lens is attached to a unfocused ultrasonic. And the acoustic lens is a cuboid prism with a concave cone on the bottom, made of fused silica. Similar to an axicon that can generate a Bessel beam, the Bessel ultrasonic transducer can produce nondiffracting Bessel ultrasonic beams. Therefore, extended depth of field with uniformly high resolution and high detection sensitivity can be obtained. We used COMSOL to simulate the transmission of ultrasonic field of the designed conical acoustic lens, and compare it with the spherical focused ultrasonic transducer. The results show that the depth of field of the Bessel ultrasonic transducer is about 8 times that of the conventional spherical focused ultrasonic transducer. And the depth of field of the Bessel ultrasonic transducer can be further adjusted by adjusting the cone angle of the conical acoustic lens. The Bessel ultrasonic transducer will help improve the capabilities of the ultrasound probe and expand its application range. For example, an ultrasonic probe with a large depth of field will expand the imaging depth of photoacoustic microscopy and enhance its ability in non-destructive testing.
In recent years, photoacoustic imaging, an emerging nondestructive biomedical imaging technology, has shown great potential for early diagnosis of diseases with its advantages of highly sensitive optical contrast and high resolution. It is a hard project to collect a large number of pathological medical images by using photoacoustic imaging. How to compress large amounts of data, rapid transmission and storage of important value information has become an urgent problem to be solved. In this paper, build a virtual simulation platform for compressed sensing photoacoustic tomography by combining compressed sensing reconstruction algorithms with photoacoustic imaging based on the k-wave simulation toolbox. On the one hand, compressed sensing can reduce sample rates, accelerated the speed of imaging. On the other hand, it can modify the demands for hardware devices and facilitate to transmit and store of data. The k-wave simulation toolbox is used to build simulation models for simulating the propagation of photoacoustic fields, recording of photoacoustic signals, and image reconstruction. We validated the performance of the simulation platform by imaging the vascular network. The results show that the virtual simulation platform compressed sensing photoacoustic tomography can achieve high-quality photoacoustic imaging with less data. The virtual platform can provide theoretical guidance for the application of compressed sensing in photoacoustic imaging.
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