In recent years, more and more organizations and teams in the world are engaged in photoacoustic imaging research. Photoacoustic imaging is in a state of vigorous development. As an important branch of photoacoustic microscopy, optical resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, which has the advantages of high resolution, high contrast, high sensitivity and non-invasiveness. However, in order to obtain high resolution, it is often necessary to focus the laser beam, which will lead to small imaging depth of field and unable to obtain large-scale structural information. However, in clinical diagnosis, doctors want to obtain large-scale and high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. In order to expand the depth of field of photoacoustic microscopy imaging, this paper proposes a three-dimensional information fusion algorithm for photoacoustic microscopy imaging. Firstly, we obtain two sets of vascular data (except the focus position) by virtual photoacoustic microscopy. Then we take out the B scan data of two sets of three-dimensional data sets in turn, and use the fusion algorithm based on pyramid transform to fuse them. Finally, the maximum projection is used to restore the original data and the fused data. We compare the maximum projection before and after fusion. The experimental results show that the algorithm realizes the extension of the depth of field, and the fused data successfully displays more abundant vascular information in an image, and maintains the advantages of high contrast and high resolution of photoacoustic microscopy imaging.
KEYWORDS: Photoacoustic microscopy, Image fusion, Information fusion, 3D photoacoustic microscopy, Photoacoustic imaging, Photoacoustic spectroscopy, Image processing, Data fusion, 3D image processing, Medical imaging
Photoacoustic imaging is a functional imaging method based on the photoacoustic effect, which combines the high contrast of optical imaging and the low dispersion characteristics of acoustic imaging. It has been developed rapidly in recent years. Photoacoustic microscopy, as an important branch, is widely used in biomedical imaging due to its high resolution, high contrast, and non-destructive characteristics. Compared with other medical imaging techniques, photoacoustic microscopy is simple, effective, low-cost, and does not generate ionizing radiation. But due to the need to focus the laser strongly, the depth of field is limited. Currently, most photoacoustic microscopy adopts an array scanning mechanism. Limited by the imaging depth of field and inherent scanning methods, photoacoustic microscopy cannot achieve large-volume, highresolution, and high-speed imaging at the same time. High-speed and large-scale tissue imaging is of great significance for the study of response mechanisms and the development of physiological and pathological processes. It is conducive to make accurate judgments for disease diagnosis. For the problems of photoacoustic microscopy, this paper proposes a highresolution three-dimensional information fusion technology suitable for photoacoustic microscopy, which provides richer structural and functional information for related physiological and pathological research. Combining the tomographic features of the data collected by the photoacoustic microscopy system with the traditional Laplacian pyramid transform, the depth of field of the photoacoustic microscopy is expanded. Two sets of single-focus image data sets of virtual photoacoustic microscopy platforms are collected and processed by three-dimensional high-resolution information fusion technology. The results demonstrates that a complete large-scale three-dimensional high-resolution structure has been successfully realized, and the reliability of the method is verified.
Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.
Photoacoustic imaging(PAI) is a emerging powerful and efficient imaging technology. Optical-resolution photoacoustic microscopy is an useful photoacoustic imaging technique combining the advantages of both optical imaging and acoustic imaging which obtains many attractive advanges such as high resolution, high contrast and so on. Laser beam is often focused strongly to achieve high resolution. However, this will lead to a poor depth-of-field and less structural information which limits the further application of this technology. Aimage fusion method based on CNN feature extraction is proposed to achieve large volumetric optical-resolution photoacoustic microscopy. First, two groups of simulated 3D photoacoustic data of different focal locations were obtained through photoacoustic microscopic imaging platform. Then B-scan data were fused and maximum projection of the reconstructed 3D data is taken to display the photoacoustic information. By comparing the source images and the fused image, we show that the proposed method can be implemented to obtain large volumetric and high-resolution photoacoustic images.
In recent years, photoacoustic imaging as a high sensitivity nondestructive testing technology has been widely studied.It can image biological tissues according to the photoacoustic effect of biological tissues and the differences in optical absorption coefficients of various parts of biological tissues.At the same time, it has the high penetration characteristics of pure ultrasonic imaging and the high contrast characteristics of pure optical imaging, which can provide high resolution and high contrast tissue imaging. Therefore, it can be used as an important means to study the structure and function information of biological tissues, and it is one of the most important real-time medical imaging technologies in the future biomedical field.However, in photoacoustic microscopy, an important branch of photoacoustic imaging, in order to obtain tissue imaging with high resolution and high contrast, it often requires strong focusing, which makes the imaging depth of field smaller and cannot obtain a wide range of biological tissue structure and function information, which is not conducive to medical diagnosis.In order to solve this problem, a three-dimensional information fusion algorithm for photoacoustic microscopy imaging is proposed in this paper.Firstly, we use the virtual photoacoustic microscopy imaging platform to generate two sets of vascular data (only the focus position is different). Then we take out the B-scan data corresponding to the three-dimensional data set, and use the fusion algorithm based on wavelet transform to fuse them in turn.Finally, we use the maximum projection to restore the original data and the fused data, and compare the maximum projection maps before and after fusion.The experimental results show that the algorithm maintains the advantages of high resolution and high contrast, extends the depth of field and obtains a wide range of clear vascular structure.
Currently, there are four major medical imaging technologies in the clinic: X-ray computer tomography (X-CT), ultrasound scan imaging (US), positron emission tomography (PET), and magnetic resonance imaging (MRI). They have developed rapidly, but they all have their own disadvantages. Compared with the above four imaging methods, the photoacoustic imaging (PAI) technology based on the photoacoustic effect has been extensively researched. PAI combines the high-contrast advantages of pure optical imaging and the high resolution of pure ultrasound imaging, which can achieve deeper imaging of biological tissues, and is currently widely used in biological imaging. The research in this paper is the expansion of the depth of field of the PAI system. The basic principle of PAI is to irradiate the target tissue with a short pulse laser, to excite ultrasound. The light absorption distribution reflecting the internal structure of the target tissue is reconstructed from the sampled sound waves. Since it needs to focus the laser strongly, this will result in a small imaging depth of field. Many biological tissues (such as brain, abdomen, etc.) have curved surfaces. Due to the limited depth of field of the optical imaging system, the blood vessels in the imaging field of view may not be on the same focal plane. It is arduous to get all accurately focused blood vessel images. It is not conducive to the observation of changes in the structure and composition of blood vessels, which brings great inconvenience to related researchers. In order to solve this problem, this paper proposes a large depth of field and high-resolution three-dimensional photoacoustic information fusion technology suitable for PAI systems. In this paper, the virtual blood vessel data sets are used to simulate the three-dimensional data sets of blood vessels at different focal positions collected by the PAI system. Based on the visualization software Amira, the two sets of three-dimensional data are reconstructed and fused. The results demonstrate that the fused virtual blood vessel imaging structure shows a complete high-resolution structure in the entire field of view. The validity and reliability of the method are verified.
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