Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results i...Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results in poor flexibility and reus- ability. Insect compound eyes offer unique advantages for moving target detection and these advantages have attracted the attention of many researchers in recent years. In this paper we proposed a new system for moving target detection. We used the detection mechanism of insect compound eyes for the simulation of the characteristics of structure, control, and function. We discussed the design scheme of the system, the development of the bionic control circuit, and introduced the proposed mathe- matical model of bionic cqmpound eyes for data acquisition and object detection. After this the integrated system was described and discussed. Our paper presents a novel approach for moving target detection. This approach effectively tackles some of the well-known problems in the field of view, resolution, and real-time processing problems in moving target detection.展开更多
Exosomes are important cancer biomarkers,however,the accuracy of exosome detection is greatly reduced due to heterogeneity of each exosome.Detecting exosomes with a larger field-of-view(FOV)might be a good solution.Co...Exosomes are important cancer biomarkers,however,the accuracy of exosome detection is greatly reduced due to heterogeneity of each exosome.Detecting exosomes with a larger field-of-view(FOV)might be a good solution.Compound eyes offer unique advantages such as a large field of view,low aberration,and high temporal resolution.Bionic compound eyes aim to replicate such features and have broad applications in fields like machine vision and medical imaging.In this paper,we propose the fabrication and application of a bionic compound eye for quantitative detection of exosomes,which allows fluorescence imaging of exosomes with an enlarged FOV,achieving a detection limit as low as 9.1×10^(2)particles/mL.The bionic compound eye is formed by simply replicating a fly eye with polydimethylsiloxane(PDMS).To detect exosomes,a microfluidic array chip compatible with the compound eye is designed.Exosomes are captured on the chip using CD63 aptamers as the capturing probes.Another kind of fluorescent aptamers are utilized to recognize the captured exosomes.Large FOV dual-color fluorescence(LFDF)imaging of these exosomes is realized by inserting the compound eye between the objective and microfluidic chip.The advantages of LFDF imaging include,first,dual-color fluorescence imaging can guarantee that we are indeed imaging exosomes;second,large FOV can reduce the impact of heterogeneity of exosomes.Thus,the reliability of assay results would be greatly improved.As a proof-of-concept,breast cancer exosomes were used as the example.The experimental results showed that,compared to imaging without the compound eye,the standard deviation of LFDF imaging results decreased by approximately 38%.Thus,the detection errors could be greatly reduced.The feasibility of using LFDF imaging for subtype classification of breast cancer exosomes was also preliminarily validated.This technology offers a new,low-cost,and highly accurate solution for exosome based cancer diagnosis.展开更多
To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this syste...To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.展开更多
基金The work presented in this paper is supported by the Scholarship for International Young Scientists of NSFC （National Natural Science Foundation of China） （1D： 41050110441）.
文摘Conventional moving target detection focuses on algorithms to improve detection efficiency. These algorithms pay less attention to the image acquisition means, and usually solve specific problems. This often results in poor flexibility and reus- ability. Insect compound eyes offer unique advantages for moving target detection and these advantages have attracted the attention of many researchers in recent years. In this paper we proposed a new system for moving target detection. We used the detection mechanism of insect compound eyes for the simulation of the characteristics of structure, control, and function. We discussed the design scheme of the system, the development of the bionic control circuit, and introduced the proposed mathe- matical model of bionic cqmpound eyes for data acquisition and object detection. After this the integrated system was described and discussed. Our paper presents a novel approach for moving target detection. This approach effectively tackles some of the well-known problems in the field of view, resolution, and real-time processing problems in moving target detection.
基金supported by the Natural Science Foundation of China(NSFC)(Nos.62175027,62175030,62205053,and 62305054).
文摘Exosomes are important cancer biomarkers,however,the accuracy of exosome detection is greatly reduced due to heterogeneity of each exosome.Detecting exosomes with a larger field-of-view(FOV)might be a good solution.Compound eyes offer unique advantages such as a large field of view,low aberration,and high temporal resolution.Bionic compound eyes aim to replicate such features and have broad applications in fields like machine vision and medical imaging.In this paper,we propose the fabrication and application of a bionic compound eye for quantitative detection of exosomes,which allows fluorescence imaging of exosomes with an enlarged FOV,achieving a detection limit as low as 9.1×10^(2)particles/mL.The bionic compound eye is formed by simply replicating a fly eye with polydimethylsiloxane(PDMS).To detect exosomes,a microfluidic array chip compatible with the compound eye is designed.Exosomes are captured on the chip using CD63 aptamers as the capturing probes.Another kind of fluorescent aptamers are utilized to recognize the captured exosomes.Large FOV dual-color fluorescence(LFDF)imaging of these exosomes is realized by inserting the compound eye between the objective and microfluidic chip.The advantages of LFDF imaging include,first,dual-color fluorescence imaging can guarantee that we are indeed imaging exosomes;second,large FOV can reduce the impact of heterogeneity of exosomes.Thus,the reliability of assay results would be greatly improved.As a proof-of-concept,breast cancer exosomes were used as the example.The experimental results showed that,compared to imaging without the compound eye,the standard deviation of LFDF imaging results decreased by approximately 38%.Thus,the detection errors could be greatly reduced.The feasibility of using LFDF imaging for subtype classification of breast cancer exosomes was also preliminarily validated.This technology offers a new,low-cost,and highly accurate solution for exosome based cancer diagnosis.
文摘To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.
