As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of u...As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio(SNR)imaging in fiber bundles,the iterative super-resolution reconstruction network based on a physical model is proposed.Under the constraint of solving the two subproblems of data fidelity and prior regularization term alternately,the network can efficiently“regenerate”the lost spatial resolution with deep learning.By building and calibrating a dual-path imaging system,the real-world dataset where paired low-resolution(LR)-high-resolution(HR)images on the same scene can be generated simultaneously.Numerical results on both the United States Air Force(USAF)resolution target and complex target objects demonstrate that the algorithm can restore high-contrast images without pixilated noise.On the basis of super-resolution reconstruction,compound eye image composition based on fiber bundle is also embedded in this paper for the actual imaging requirements.The proposed work is the first to apply a physical model-based deep learning network to fiber bundle imaging in the infrared band,effectively promoting the engineering application of thermal radiation detection.展开更多
Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral images.Most spectral unmixi...Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral images.Most spectral unmixing methods are globally based and do not consider the spectral variability among its endmembers that occur due to illumination,atmospheric,and environmental conditions.Here,endmember bundle extraction plays a major role in overcoming the above-mentioned limitations leading to more accurate abundance fractions.Accordingly,a two-stage approach is proposed to extract endmembers through endmember bundles in hyperspectral images.The divide and conquer method is applied as the first step in subset images with only the non-redundant bands to extract endmembers using the Vertex Component Analysis(VCA)and N-FINDR algorithms.A fuzzy rule-based inference system utilizing spectral matching parameters is proposed in the second step to categorize endmembers.The endmember with the minimum error is chosen as the final endmember in each specific category.The proposed method is simple and automatically considers endmember variability in hyperspectral images.The efficiency of the proposed method is evaluated using two real hyperspectral datasets.The average spectral angle and abundance angle are used to analyze the performance measures.展开更多
A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constrai...A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.展开更多
We propose a method of reliable tracking orientation and flexible step size fiber tracking. A new directional strategy was defined to select one optimal tracking orientation from each directional set, which was based ...We propose a method of reliable tracking orientation and flexible step size fiber tracking. A new directional strategy was defined to select one optimal tracking orientation from each directional set, which was based on the single-tensor model and the two-tensor model. The directional set of planar voxels contained three tracking directions: two from the two-tensor model and one from the single- tensor model. The directional set of linear voxels contained only one principal vector. In addition, a flexible step size, rather than fixable step sizes, was implemented to improve the accuracy of fiber tracking. We used two sets of human data to assess the performance of our method; one was from a healthy volunteer and the other from a patient with low-grade glioma. Results verified that our method was superior to the single-tensor Fiber Assignment by Continuous Tracking and the two-tensor eXtended Streamline Tractography for showing detailed images of fiber bundles.展开更多
Objective:Indocyanine green(ICG)with near-infrared fluorescence absorption is approved by the United States Food and Drug Administration for clinical applications in angiography,blood flow evaluation,and liver functio...Objective:Indocyanine green(ICG)with near-infrared fluorescence absorption is approved by the United States Food and Drug Administration for clinical applications in angiography,blood flow evaluation,and liver function assessment.It has strong optical absorption in the near-infrared region,where light can penetrate deepest into biological tissue.We sought to review its value in guiding prostate cancer treatment.Methods:All related literature at PubMed from January 2000 to December 2020 were reviewed.Results:Multiple preclinical studies have demonstrated the usefulness of ICG in identifying prostate cancer by using different engineering techniques.Clinical studies have demonstrated the usefulness of ICG in guiding sentinel node dissection during radical prostatectomy,and possible better preservation of neurovascular bundle by identifying landmark prostatic arteries.New techniques such as adding fluorescein in additional to ICG were tested in a limited number of patients with encouraging result.In addition,the use of the ICG was shown to be safe.Even though there are encouraging results,it does not carry sufficient sensitivity and specificity in replacing extended pelvic lymph node dissection during radical prostatectomy.Conclusion:Multiple preclinical and clinical studies have shown the usefulness of ICG in identifying and guiding treatment for prostate cancer.Larger randomized prospective studies are warranted to further test its usefulness and find new modified approaches.展开更多
基金the National Natural Science Foundation of China(Grant Nos.61905115,62105151,62175109,U21B2033)Leading Technology of Jiangsu Basic Research Plan(Grant No.BK20192003)+2 种基金Youth Foundation of Jiangsu Province(Grant Nos.BK20190445,BK20210338)Fundamental Research Funds for the Central Universities(Grant No.30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(Grant No.JSGP202105)to provide fund for conducting experiments。
文摘As the representative of flexibility in optical imaging media,in recent years,fiber bundles have emerged as a promising architecture in the development of compact visual systems.Dedicated to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio(SNR)imaging in fiber bundles,the iterative super-resolution reconstruction network based on a physical model is proposed.Under the constraint of solving the two subproblems of data fidelity and prior regularization term alternately,the network can efficiently“regenerate”the lost spatial resolution with deep learning.By building and calibrating a dual-path imaging system,the real-world dataset where paired low-resolution(LR)-high-resolution(HR)images on the same scene can be generated simultaneously.Numerical results on both the United States Air Force(USAF)resolution target and complex target objects demonstrate that the algorithm can restore high-contrast images without pixilated noise.On the basis of super-resolution reconstruction,compound eye image composition based on fiber bundle is also embedded in this paper for the actual imaging requirements.The proposed work is the first to apply a physical model-based deep learning network to fiber bundle imaging in the infrared band,effectively promoting the engineering application of thermal radiation detection.
文摘Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral images.Most spectral unmixing methods are globally based and do not consider the spectral variability among its endmembers that occur due to illumination,atmospheric,and environmental conditions.Here,endmember bundle extraction plays a major role in overcoming the above-mentioned limitations leading to more accurate abundance fractions.Accordingly,a two-stage approach is proposed to extract endmembers through endmember bundles in hyperspectral images.The divide and conquer method is applied as the first step in subset images with only the non-redundant bands to extract endmembers using the Vertex Component Analysis(VCA)and N-FINDR algorithms.A fuzzy rule-based inference system utilizing spectral matching parameters is proposed in the second step to categorize endmembers.The endmember with the minimum error is chosen as the final endmember in each specific category.The proposed method is simple and automatically considers endmember variability in hyperspectral images.The efficiency of the proposed method is evaluated using two real hyperspectral datasets.The average spectral angle and abundance angle are used to analyze the performance measures.
基金supported by the National Natural Science Foundations of China (Nos.41101441,60974107, 41471381)the Foundation of Graduate Innovation Center in NUAA(No.kfjj130133)
文摘A bundle adjustment method of remote sensing images based on dual quaternion is presented,which conducted the uniform disposal corresponding location and attitude of sequence images by the dual quaternion.The constraint relationship of image itself and sequence images is constructed to compensate the systematic errors.The feasibility of this method used in bundle adjustment is theoretically tested by the analysis of the structural characteristics of error equation and normal equation based on dual quaternion.Different distributions of control points and stepwise regression analysis are introduced into the experiment for RC30 image.The results show that the adjustment accuracy can achieve 0.2min plane and 1min elevation.As a result,this method provides a new technique for geometric location problem of remote sensing images.
文摘针对传统的传像系统易受电磁干扰的问题,设计并实现了在特殊环境下使用的光纤束传像系统。利用ZEMAX光学仿真软件,设计出了一个工作波段为可见光,全视场80°,焦距为5 mm的监控物镜。该物镜各视场光学调制传递函数(Modulation Transfer Function,MTF)值在空间频率36 lp/mm处大于0.8,点列图最大弥散斑均方根半径(RMSradius)为3.031μm,接近衍射极限,因此具有较高成像质量。采用加工的物镜、选型转接镜及光纤束等核心器件,搭建了传像系统。通过测试光纤束图像传输系统的抗电磁干扰性能,采用高斯低通滤波结合DCT同态滤波算法有效去除图像的像素,获得了高质量的信息传输效果。
基金supported by the Science and Technology Commission of the Shanghai Municipality of China,No.10dz2211800,No.10XD1421400the National High Technology Research and Development Program,No.2009AA02Z415the Innovation Program of Shanghai Municipal Education Commission,No.11yz292
文摘We propose a method of reliable tracking orientation and flexible step size fiber tracking. A new directional strategy was defined to select one optimal tracking orientation from each directional set, which was based on the single-tensor model and the two-tensor model. The directional set of planar voxels contained three tracking directions: two from the two-tensor model and one from the single- tensor model. The directional set of linear voxels contained only one principal vector. In addition, a flexible step size, rather than fixable step sizes, was implemented to improve the accuracy of fiber tracking. We used two sets of human data to assess the performance of our method; one was from a healthy volunteer and the other from a patient with low-grade glioma. Results verified that our method was superior to the single-tensor Fiber Assignment by Continuous Tracking and the two-tensor eXtended Streamline Tractography for showing detailed images of fiber bundles.
文摘Objective:Indocyanine green(ICG)with near-infrared fluorescence absorption is approved by the United States Food and Drug Administration for clinical applications in angiography,blood flow evaluation,and liver function assessment.It has strong optical absorption in the near-infrared region,where light can penetrate deepest into biological tissue.We sought to review its value in guiding prostate cancer treatment.Methods:All related literature at PubMed from January 2000 to December 2020 were reviewed.Results:Multiple preclinical studies have demonstrated the usefulness of ICG in identifying prostate cancer by using different engineering techniques.Clinical studies have demonstrated the usefulness of ICG in guiding sentinel node dissection during radical prostatectomy,and possible better preservation of neurovascular bundle by identifying landmark prostatic arteries.New techniques such as adding fluorescein in additional to ICG were tested in a limited number of patients with encouraging result.In addition,the use of the ICG was shown to be safe.Even though there are encouraging results,it does not carry sufficient sensitivity and specificity in replacing extended pelvic lymph node dissection during radical prostatectomy.Conclusion:Multiple preclinical and clinical studies have shown the usefulness of ICG in identifying and guiding treatment for prostate cancer.Larger randomized prospective studies are warranted to further test its usefulness and find new modified approaches.