POLAR-2 is a gamma-ray burst(GRB)polarimeter that is designed to study the polarization in GRB radiation emissions,aiming to improve our knowledge of related mechanisms.POLAR-2 is expected to utilize an on-board polar...POLAR-2 is a gamma-ray burst(GRB)polarimeter that is designed to study the polarization in GRB radiation emissions,aiming to improve our knowledge of related mechanisms.POLAR-2 is expected to utilize an on-board polarimeter that is sensitive to soft X-rays(2-10 keV),called low-energy polarization detector.We have developed a new soft X-ray polari-zation detector prototype based on gas microchannel plates(GMCPs)and pixel chips(Topmetal).The GMCPs have bulk resistance,which prevents charging-up effects and ensures gain stability during operation.The detector is composed of low outgassing materials and is gas-sealed using a laser welding technique,ensuring long-term stability.A modulation factor of 41.28%±0.64% is obtained for a 4.5 keV polarized X-ray beam.A residual modulation of 1.96%±0.58% at 5.9 keV is observed for the entire sensitive area.展开更多
After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve we...After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.展开更多
The exact radar cross-section （RCS） measurement is difficult when the scattering of targets is low. Ful polarimetric cali-bration is one technique that offers the potential for improving the accuracy of RCS measurem...The exact radar cross-section （RCS） measurement is difficult when the scattering of targets is low. Ful polarimetric cali-bration is one technique that offers the potential for improving the accuracy of RCS measurements. There are numerous polarimetric calibration algorithms. Some complex expressions in these algo-rithms cannot be easily used in an engineering practice. A radar polarimetric coefficients matrix （RPCM） with a simpler expression is presented for the monostatic radar polarization scattering matrix （PSM） measurement. Using a rhombic dihedral corner reflector and a metal ic sphere, the RPCM can be obtained by solving a set of equations, which can be used to find the true PSM for any target. An example for the PSM of a metal ic dish shows that the proposed method obviously improves the accuracy of cross-polarized RCS measurements.展开更多
Imaging polarimetry is one of the most widely used analytical technologies for object detection and analysis.To date,most metasurface-based polarimetry techniques are severely limited by narrow operating bandwidths an...Imaging polarimetry is one of the most widely used analytical technologies for object detection and analysis.To date,most metasurface-based polarimetry techniques are severely limited by narrow operating bandwidths and inevitable crosstalk,leading to detrimental effects on imaging quality and measurement accuracy.Here,we propose a crosstalkfree broadband achromatic full Stokes imaging polarimeter consisting of polarization-sensitive dielectric metalenses,implemented by the principle of polarization-dependent phase optimization.Compared with the single-polarization optimization method,the average crosstalk has been reduced over three times under incident light with arbitrary polarization ranging from 9μm to 12μm,which guarantees the measurement of the polarization state more precisely.The experimental results indicate that the designed polarization-sensitive metalenses can effectively eliminate the chromatic aberration with polarization selectivity and negligible crosstalk.The measured average relative errors are 7.08%,8.62%,7.15%,and 7.59%at 9.3,9.6,10.3,and 10.6μm,respectively.Simultaneously,the broadband full polarization imaging capability of the device is also verified.This work is expected to have potential applications in wavefront detection,remote sensing,light-field imaging,and so forth.展开更多
A new hybrid Freeman/eigenvalue decomposition based on the orientation angle compensation and the various extended volume models for polarimetric synthetic aperture radar(PolSAR) data are presented. There are three st...A new hybrid Freeman/eigenvalue decomposition based on the orientation angle compensation and the various extended volume models for polarimetric synthetic aperture radar(PolSAR) data are presented. There are three steps in the novel version of the three-component model-based decomposition.Firstly, two special unitary transform matrices are applied on the coherency matrix for deorientation to decrease the correlation between the co-polarized term and the cross-polarized term.Secondly, two new conditions are proposed to distinguish the manmade structures and the nature media after the orientation angle compensation. Finally, in order to adapt to the scattering properties of different media, five different volume scattering models are used to decompose the coherency matrix. These new conditions pre-resolves man-made structures, which is beneficial to the subsequent selection of a more suitable volume scattering model.Fully PolSAR data on San Francisco are used in the experiments to prove the efficiency of the proposed hybrid Freeman/eigenvalue decomposition.展开更多
The C-band synthetic aperture radar（SAR） data from the Bohai Sea of China, the Labrador Sea in the Arctic and the Weddell Sea in the Antarctic are used to analyze and discuss the sea ice full polarimetric informatio...The C-band synthetic aperture radar（SAR） data from the Bohai Sea of China, the Labrador Sea in the Arctic and the Weddell Sea in the Antarctic are used to analyze and discuss the sea ice full polarimetric information reconstruction ability under compact polarimetric modes. The type of compact polarimetric mode which has the highest reconstructed accuracy is analyzed, along with the performance impact of the reconstructed pseudo quad-pol SAR data on the sea ice detection and sea ice classification. According to the assessment and analysis, it is recommended to adopt the CTLR mode for reconstructing the polarimetric parameters σ_（HH）~0,σ_（VV）~0, H and α,while for reconstructing the polarimetric parameters σ_（HV）~0, ρ_（H-V）, λ_1 and λ_2, it is recommended to use the π/4 mode.Moreover, it is recommended to use the π/4 mode in studying the action effects between the electromagnetic waves and sea ice, but it is recommended to use the CTLR mode for studying the sea ice classification.展开更多
An improved algorithm for multi-polarization reconstruction from compact polarimetry （CP） is proposed. According to two fundamental assumptions in compact polarimetric reconstruction, two improvements are proposed. ...An improved algorithm for multi-polarization reconstruction from compact polarimetry （CP） is proposed. According to two fundamental assumptions in compact polarimetric reconstruction, two improvements are proposed. Firstly, the four-component model-based decomposition algorithm is modified with a new volume scattering model. The decomposed helix scattering component is then used to deal with the non-reflection symmetry condition in compact polarimetric measurements. Using the decomposed power and considering the scattering mechanism of each component, an average relationship between copolarized and crosspolarized channels is developed over the original polarization state extrapolation model. E-SAR polarimetric data acquired over the Oberpfaffenhofen area and JPL/AIRSAR polarimetric data acquired over San Francisco are used for verification, and good reconstruction results are obtained, demonstrating the effectiveness of the proposed algorithm.展开更多
Powdery mildew is a disease that threatens wheat production and causes severe economic losses worldwide. Its timely diagnosis is imperative for preventing and controlling its spread. In this study, the multiangle cano...Powdery mildew is a disease that threatens wheat production and causes severe economic losses worldwide. Its timely diagnosis is imperative for preventing and controlling its spread. In this study, the multiangle canopy spectra and disease severity of wheat were investigated at several developmental stages and degrees of disease severity. Four wavelength variable-selected algorithms: successive projection(SPA), competitive adaptive reweighted sampling(CARS), feature selection learning(Relief-F), and genetic algorithm(GA), were used to identify bands sensitive to powdery mildew. The wavelength variables selected were used as input variables for partial least squares(PLS), extreme learning machine(ELM), random forest(RF), and support vector machine(SVM) algorithms, to construct a suitable prediction model for powdery mildew. Spectral reflectance and conventional vegetation indices(VIs) displayed angle effects under several disease severity indices(DIs). The CARS method selected relatively few wavelength variables and showed a relatively homogeneous distribution across the 13 viewing zenith angles.Overall accuracies of the four modeling algorithms were ranked as follows: ELM(0.70–0.82) > PLS(0.63–0.79) > SVM(0.49–0.69) > RF(0.43–0.69). Combinations of features and algorithms generated varied accuracies, with coefficients of determination(R^(2)) single-peaked at different observation angles. The constructed CARS-ELM model extracted a predictable bivariate relationship between the multi-angle canopy spectrum and disease severity, yielding an R^(2)> 0.8 at each measured angle. Especially for larger angles,monitoring accuracies were increased relative to the optimal VI model(40% at-60°, 33% at +60°), indicating that the CARS-ELM model is suitable for extreme angles of-60° and +60°. The results are proposed to provide a technical basis for rapid and large-scale monitoring of wheat powdery mildew.展开更多
Purpoe: To evaluate retinal nerve fiber layer (RNFL) thickness measurements in local normal Chinese subjects of different age groups and analyse the correlation of RNFL thickness with age using scanning laser polarime...Purpoe: To evaluate retinal nerve fiber layer (RNFL) thickness measurements in local normal Chinese subjects of different age groups and analyse the correlation of RNFL thickness with age using scanning laser polarimetry (SLP,GDxVCC). To assess the reproducibility of RNFL thickness measurement with GDxVCC. Methods: The RNFL thickness of 67 normal subjects (123 eyes) were measured by GDxVCC. The average TSNIT parameters were calculated. The differences of RNFL thickness between sex,right and left eyes,superior and inferior were compared. The relationship between RNFL thickness and age was analyzed with correlation analysis and linear regression analysis. The intraclass correlation coefficients (ICC) of three images in every eye were calculated. Results: The average peripapillary RNFL thickness at the superior,inferior and whole ellipse regions in 123 eyes of 67 normal subjects were (70.30±6.76)(?)m,(67.35±6.77)(?)m and (56.87±4.53)(?) m,respectively. The average TNSIT standard deviation was 23.68±4.61 and the average inter-eye symmetric value was 0.86±0.11. There were significant difference of RNFL thickness between superior and inferior (t=4.952,P < 0.001). There were significant difference of inferior RNFL thickness and TNSIT standard deviation between right and left eyes (P=0.005 and 0.002),while not significant difference of superior RNFL thickness and whole mean RNFL thickness between right and left eye (P=0.086 and 0.529). There was no significant difference in TSNIT parameters between different genders. There was a slight negative correlation average RNFL thickness in superior sector with age (decreased approximately 0.15 microns per year,P=0.047) in the subjects aged below 60 years old. The ICC values of RNFL thickness were >0.8 in superior,inferior and global. Conclusions: The RNFL thickness can be measured accurately by GDxVCC and the reproducibility of RNFL thickness measurement by GDxVCC is good. There was a slight negative correlation between average RNFL thickness in superior with age. More researches on the effects of age on RNFL thickness by GDxVCC are needed.展开更多
High-grade squamous intraepithelial lesion(HSIL)is regarded as a serious precancerous state of cervix,and it is easy to progress into cervical invasive carcinoma which highlights the importance of earlier diagnosis an...High-grade squamous intraepithelial lesion(HSIL)is regarded as a serious precancerous state of cervix,and it is easy to progress into cervical invasive carcinoma which highlights the importance of earlier diagnosis and treatment of cervical lesions.Pathologists examine the biopsied cervical epithelial tissue through a microscope.The pathological examination will take a long time and sometimes results in high inter-and intra-observer variability in outcomes.Polarization imaging techniques have broad application prospects for biomedical diagnosis such as breast,liver,colon,thyroid and so on.In our team,we have derived polarimetry feature parameters(PFPs)to characterize microstructural features in histological sections of breast tissues,and the accuracy for PFPs ranges from 0.82 to 0.91.Therefore,the aim of this paper is to distinguish automatically microstructural features between HSIL and cervical squamous cell carcinoma(CSCC)by means of polarization imaging techniques,and try to provide quantitative reference index for patho-logical diagnosis which can alleviate the workload of pathologists.Polarization images of the H&E stained histological slices were obtained by Mueller matrix microscope.The typical path-ological structure area was labeled by two experienced pathologists.Calculate the polarimetry basis parameter(PBP)statistics for this region.The PBP statistics(stat PBPs)are screened by mutual information(MI)method.The training method is based on a linear discriminant analysis(LDA)classier whichnds the most simplied linear combination from these stat PBPs and the accuracy remains constant to characterize the specic microstructural feature quantitatively in cervical squamous epithelium.We present results from 37 clinical patients with analysis regions of cervical squamous epithelium.The accuracy of PFP for recognizing HSIL and CSCC was 83.8%and 87.5%,respectively.This work demonstrates the ability of PFP to quantitatively charac-terize the cervical squamous epithelial lesions in the H&E pathological sections.Signicance:Polarization detection technology provides an effcient method for digital pathological diagnosis and points out a new way for automatic screening of pathological sections.展开更多
In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage o...In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classifica-tion accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by ex-periments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.展开更多
A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix ...A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.展开更多
This paper investigates the ability of the depolarization degree, derived from the characteristic polarization states at the resonant frequency set, to identify corner or swept, i.e. dihedral, changes in same-class ta...This paper investigates the ability of the depolarization degree, derived from the characteristic polarization states at the resonant frequency set, to identify corner or swept, i.e. dihedral, changes in same-class targets by a metallic wire example. A well-estimated depolarization degree requires a robust extraction of the fundamental target resonance set in two orthogonal sets of fully co-polarized and cross-polarized polarization channels, then finding the null polarization states using the Lagrangian method. Such depolarization degree per resonance mode has the potential to form a robust feature set because it is relatively less sensitive to onset ambiguity, invariant to rotation, and could create a compact, recognizable, and separable distribution in the proposed feature space. The study was limited to two targets with two swept changes of fifteen degrees within normal incidence;under a supervised learning approach, the results showed that the identification rate converging to upper-bound (100%) for a signal-to-noise ratio above 20 dB and lower-bound around (50%) below −10 dB.展开更多
基金supported by Department of Physics and GXUNAOC Center for Astrophysics and Space Sciences,Guangxi UniversityThe National Natural Science Foundation of China(Nos.12027803,U1731239,12133003,12175241,U1938201,U1732266)the Guangxi Science Foundation(Nos.2018GXNSFGA281007,2018JJA110048).
文摘POLAR-2 is a gamma-ray burst(GRB)polarimeter that is designed to study the polarization in GRB radiation emissions,aiming to improve our knowledge of related mechanisms.POLAR-2 is expected to utilize an on-board polarimeter that is sensitive to soft X-rays(2-10 keV),called low-energy polarization detector.We have developed a new soft X-ray polari-zation detector prototype based on gas microchannel plates(GMCPs)and pixel chips(Topmetal).The GMCPs have bulk resistance,which prevents charging-up effects and ensures gain stability during operation.The detector is composed of low outgassing materials and is gas-sealed using a laser welding technique,ensuring long-term stability.A modulation factor of 41.28%±0.64% is obtained for a 4.5 keV polarized X-ray beam.A residual modulation of 1.96%±0.58% at 5.9 keV is observed for the entire sensitive area.
基金supported by the NOAA (Grant Nos. NA16AOR4320115 and NA11OAR4320072)NSF (Grant No. AGS-1341878)
文摘After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.
基金supported by the National Basic Research Program of China(973 Program)(2010CB731905)
文摘The exact radar cross-section （RCS） measurement is difficult when the scattering of targets is low. Ful polarimetric cali-bration is one technique that offers the potential for improving the accuracy of RCS measurements. There are numerous polarimetric calibration algorithms. Some complex expressions in these algo-rithms cannot be easily used in an engineering practice. A radar polarimetric coefficients matrix （RPCM） with a simpler expression is presented for the monostatic radar polarization scattering matrix （PSM） measurement. Using a rhombic dihedral corner reflector and a metal ic sphere, the RPCM can be obtained by solving a set of equations, which can be used to find the true PSM for any target. An example for the PSM of a metal ic dish shows that the proposed method obviously improves the accuracy of cross-polarized RCS measurements.
基金Sichuan Science and Technology Program(2020YFJ0001)the National Natural Science Foundation of China(61975210,62222513)+1 种基金National Key Research and Development Program(SQ2021YFA1400121)China Postdoctoral Science Foundation(2021T140670)
文摘Imaging polarimetry is one of the most widely used analytical technologies for object detection and analysis.To date,most metasurface-based polarimetry techniques are severely limited by narrow operating bandwidths and inevitable crosstalk,leading to detrimental effects on imaging quality and measurement accuracy.Here,we propose a crosstalkfree broadband achromatic full Stokes imaging polarimeter consisting of polarization-sensitive dielectric metalenses,implemented by the principle of polarization-dependent phase optimization.Compared with the single-polarization optimization method,the average crosstalk has been reduced over three times under incident light with arbitrary polarization ranging from 9μm to 12μm,which guarantees the measurement of the polarization state more precisely.The experimental results indicate that the designed polarization-sensitive metalenses can effectively eliminate the chromatic aberration with polarization selectivity and negligible crosstalk.The measured average relative errors are 7.08%,8.62%,7.15%,and 7.59%at 9.3,9.6,10.3,and 10.6μm,respectively.Simultaneously,the broadband full polarization imaging capability of the device is also verified.This work is expected to have potential applications in wavefront detection,remote sensing,light-field imaging,and so forth.
基金supported by the National Natural Science Foundation of China(41704118 11747032)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province of China(2017JQ6065 2017JQ4017)the Special Scientific Research Project of Shaanxi Provincial Education Department(18JK0549)
文摘A new hybrid Freeman/eigenvalue decomposition based on the orientation angle compensation and the various extended volume models for polarimetric synthetic aperture radar(PolSAR) data are presented. There are three steps in the novel version of the three-component model-based decomposition.Firstly, two special unitary transform matrices are applied on the coherency matrix for deorientation to decrease the correlation between the co-polarized term and the cross-polarized term.Secondly, two new conditions are proposed to distinguish the manmade structures and the nature media after the orientation angle compensation. Finally, in order to adapt to the scattering properties of different media, five different volume scattering models are used to decompose the coherency matrix. These new conditions pre-resolves man-made structures, which is beneficial to the subsequent selection of a more suitable volume scattering model.Fully PolSAR data on San Francisco are used in the experiments to prove the efficiency of the proposed hybrid Freeman/eigenvalue decomposition.
基金The National Science Foundation for Young Scientists of China under contract No.41306193the National Special Research Fund for Non-profit Marine Sector under contract No.201305025-2the Dragon 3 Cooperation Programme under contract No.10501 by the Ministry of Science and Technology of the P.R.China and the European Space Agency
文摘The C-band synthetic aperture radar（SAR） data from the Bohai Sea of China, the Labrador Sea in the Arctic and the Weddell Sea in the Antarctic are used to analyze and discuss the sea ice full polarimetric information reconstruction ability under compact polarimetric modes. The type of compact polarimetric mode which has the highest reconstructed accuracy is analyzed, along with the performance impact of the reconstructed pseudo quad-pol SAR data on the sea ice detection and sea ice classification. According to the assessment and analysis, it is recommended to adopt the CTLR mode for reconstructing the polarimetric parameters σ_（HH）~0,σ_（VV）~0, H and α,while for reconstructing the polarimetric parameters σ_（HV）~0, ρ_（H-V）, λ_1 and λ_2, it is recommended to use the π/4 mode.Moreover, it is recommended to use the π/4 mode in studying the action effects between the electromagnetic waves and sea ice, but it is recommended to use the CTLR mode for studying the sea ice classification.
基金supported by the National Natural Science Foundation of China(41171317)the State Key Program of the Natural Science Foundation of China(61132008)the Research Foundation of Tsinghua University
文摘An improved algorithm for multi-polarization reconstruction from compact polarimetry （CP） is proposed. According to two fundamental assumptions in compact polarimetric reconstruction, two improvements are proposed. Firstly, the four-component model-based decomposition algorithm is modified with a new volume scattering model. The decomposed helix scattering component is then used to deal with the non-reflection symmetry condition in compact polarimetric measurements. Using the decomposed power and considering the scattering mechanism of each component, an average relationship between copolarized and crosspolarized channels is developed over the original polarization state extrapolation model. E-SAR polarimetric data acquired over the Oberpfaffenhofen area and JPL/AIRSAR polarimetric data acquired over San Francisco are used for verification, and good reconstruction results are obtained, demonstrating the effectiveness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China (31971791)the National Key Research and Development Program of China (2017YFD0300204)。
文摘Powdery mildew is a disease that threatens wheat production and causes severe economic losses worldwide. Its timely diagnosis is imperative for preventing and controlling its spread. In this study, the multiangle canopy spectra and disease severity of wheat were investigated at several developmental stages and degrees of disease severity. Four wavelength variable-selected algorithms: successive projection(SPA), competitive adaptive reweighted sampling(CARS), feature selection learning(Relief-F), and genetic algorithm(GA), were used to identify bands sensitive to powdery mildew. The wavelength variables selected were used as input variables for partial least squares(PLS), extreme learning machine(ELM), random forest(RF), and support vector machine(SVM) algorithms, to construct a suitable prediction model for powdery mildew. Spectral reflectance and conventional vegetation indices(VIs) displayed angle effects under several disease severity indices(DIs). The CARS method selected relatively few wavelength variables and showed a relatively homogeneous distribution across the 13 viewing zenith angles.Overall accuracies of the four modeling algorithms were ranked as follows: ELM(0.70–0.82) > PLS(0.63–0.79) > SVM(0.49–0.69) > RF(0.43–0.69). Combinations of features and algorithms generated varied accuracies, with coefficients of determination(R^(2)) single-peaked at different observation angles. The constructed CARS-ELM model extracted a predictable bivariate relationship between the multi-angle canopy spectrum and disease severity, yielding an R^(2)> 0.8 at each measured angle. Especially for larger angles,monitoring accuracies were increased relative to the optimal VI model(40% at-60°, 33% at +60°), indicating that the CARS-ELM model is suitable for extreme angles of-60° and +60°. The results are proposed to provide a technical basis for rapid and large-scale monitoring of wheat powdery mildew.
文摘Purpoe: To evaluate retinal nerve fiber layer (RNFL) thickness measurements in local normal Chinese subjects of different age groups and analyse the correlation of RNFL thickness with age using scanning laser polarimetry (SLP,GDxVCC). To assess the reproducibility of RNFL thickness measurement with GDxVCC. Methods: The RNFL thickness of 67 normal subjects (123 eyes) were measured by GDxVCC. The average TSNIT parameters were calculated. The differences of RNFL thickness between sex,right and left eyes,superior and inferior were compared. The relationship between RNFL thickness and age was analyzed with correlation analysis and linear regression analysis. The intraclass correlation coefficients (ICC) of three images in every eye were calculated. Results: The average peripapillary RNFL thickness at the superior,inferior and whole ellipse regions in 123 eyes of 67 normal subjects were (70.30±6.76)(?)m,(67.35±6.77)(?)m and (56.87±4.53)(?) m,respectively. The average TNSIT standard deviation was 23.68±4.61 and the average inter-eye symmetric value was 0.86±0.11. There were significant difference of RNFL thickness between superior and inferior (t=4.952,P < 0.001). There were significant difference of inferior RNFL thickness and TNSIT standard deviation between right and left eyes (P=0.005 and 0.002),while not significant difference of superior RNFL thickness and whole mean RNFL thickness between right and left eye (P=0.086 and 0.529). There was no significant difference in TSNIT parameters between different genders. There was a slight negative correlation average RNFL thickness in superior sector with age (decreased approximately 0.15 microns per year,P=0.047) in the subjects aged below 60 years old. The ICC values of RNFL thickness were >0.8 in superior,inferior and global. Conclusions: The RNFL thickness can be measured accurately by GDxVCC and the reproducibility of RNFL thickness measurement by GDxVCC is good. There was a slight negative correlation between average RNFL thickness in superior with age. More researches on the effects of age on RNFL thickness by GDxVCC are needed.
基金the Guangming District Economic Development Special Fund(2020R01043)。
文摘High-grade squamous intraepithelial lesion(HSIL)is regarded as a serious precancerous state of cervix,and it is easy to progress into cervical invasive carcinoma which highlights the importance of earlier diagnosis and treatment of cervical lesions.Pathologists examine the biopsied cervical epithelial tissue through a microscope.The pathological examination will take a long time and sometimes results in high inter-and intra-observer variability in outcomes.Polarization imaging techniques have broad application prospects for biomedical diagnosis such as breast,liver,colon,thyroid and so on.In our team,we have derived polarimetry feature parameters(PFPs)to characterize microstructural features in histological sections of breast tissues,and the accuracy for PFPs ranges from 0.82 to 0.91.Therefore,the aim of this paper is to distinguish automatically microstructural features between HSIL and cervical squamous cell carcinoma(CSCC)by means of polarization imaging techniques,and try to provide quantitative reference index for patho-logical diagnosis which can alleviate the workload of pathologists.Polarization images of the H&E stained histological slices were obtained by Mueller matrix microscope.The typical path-ological structure area was labeled by two experienced pathologists.Calculate the polarimetry basis parameter(PBP)statistics for this region.The PBP statistics(stat PBPs)are screened by mutual information(MI)method.The training method is based on a linear discriminant analysis(LDA)classier whichnds the most simplied linear combination from these stat PBPs and the accuracy remains constant to characterize the specic microstructural feature quantitatively in cervical squamous epithelium.We present results from 37 clinical patients with analysis regions of cervical squamous epithelium.The accuracy of PFP for recognizing HSIL and CSCC was 83.8%and 87.5%,respectively.This work demonstrates the ability of PFP to quantitatively charac-terize the cervical squamous epithelial lesions in the H&E pathological sections.Signicance:Polarization detection technology provides an effcient method for digital pathological diagnosis and points out a new way for automatic screening of pathological sections.
基金Supported by the University Doctorate Special Research Fund (No. 20030614001) and the Youth Scholarship Leader Fund of Univ. of Electro. Sci. and Tech. of China.
文摘In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classifica-tion accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by ex-periments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data.
基金supported in part by the National Natural Science Fundation of China(4117131761132008+1 种基金61490693)Aeronautical Science Foundation of China(20132058003)
文摘A novel method is proposed for the supervised classification of multifrequency polarimetric synthetic aperture radar （PolSAR） images. The coherency matrices in P-, L-, and C-bands are mapped onto a 9×9 matrix Ω based on the eigenvalue decomposition of the coherency matrix of each band. A boxcar filter is then performed on the matrix Ω. The filtered data are put into a complex Wishart classifier. Finally, the effectiveness of the proposed method is demonstrated with JPL/AIRSAR multifrequency PolSAR data acquired over the Flevoland area.
文摘This paper investigates the ability of the depolarization degree, derived from the characteristic polarization states at the resonant frequency set, to identify corner or swept, i.e. dihedral, changes in same-class targets by a metallic wire example. A well-estimated depolarization degree requires a robust extraction of the fundamental target resonance set in two orthogonal sets of fully co-polarized and cross-polarized polarization channels, then finding the null polarization states using the Lagrangian method. Such depolarization degree per resonance mode has the potential to form a robust feature set because it is relatively less sensitive to onset ambiguity, invariant to rotation, and could create a compact, recognizable, and separable distribution in the proposed feature space. The study was limited to two targets with two swept changes of fifteen degrees within normal incidence;under a supervised learning approach, the results showed that the identification rate converging to upper-bound (100%) for a signal-to-noise ratio above 20 dB and lower-bound around (50%) below −10 dB.
