Fuzzy c-means （FCM） algorithm is one of the most popular methods for image segmentation. However, the standard FCM algorithm is sensitive to noise because of not taking into account the spatial information in the im...Fuzzy c-means （FCM） algorithm is one of the most popular methods for image segmentation. However, the standard FCM algorithm is sensitive to noise because of not taking into account the spatial information in the image. An improved FCM algorithm is proposed to improve the antinoise performance of FCM algorithm. The new algorithm is formulated by incorporating the spatial neighborhood information into the membership function for clustering. The distribution statistics of the neighborhood pixels and the prior probability are used to form a new membership func- tion. It is not only effective to remove the noise spots but also can reduce the misclassified pixels. Experimental results indicate that the proposed algorithm is more accurate and robust to noise than the standard FCM algorithm.展开更多
A wide range of techniques has been developed to image biological samples at high spatial and temporal resolution.In this paper,we report recent results from deep-UV confocal fAuorescence microscopy to image inherent ...A wide range of techniques has been developed to image biological samples at high spatial and temporal resolution.In this paper,we report recent results from deep-UV confocal fAuorescence microscopy to image inherent emission from fuorophores such as tryptophan,and structured ilumination microscopy(SIM)of biological materials.One motivation for developing deep-UV fhuorescence imaging and SIM is to provide methods to complement our measurements in the emerging field of X-ray coherent diffractive imaging.展开更多
To attain the volumetric information of the optic radiation in normal human brains, we per- formed diffusion tensor imaging examination in 13 healthy volunteers. Simultaneously, we used a brain normalization method to...To attain the volumetric information of the optic radiation in normal human brains, we per- formed diffusion tensor imaging examination in 13 healthy volunteers. Simultaneously, we used a brain normalization method to reduce individual brain variation and increase the accuracy of volumetric information analysis. In addition, tractography-based group mapping method was also used to investigate the probability and distribution of the optic radiation pathways. Our results showed that the measured optic radiation fiber tract volume was a range of about 0.16% and that the fractional anisotropy value was about 0.53. Moreover, the optic radiation probability fiber pathway that was determined with diffusion tensor tractography-based group mapping was able to detect the location relatively accurately. We believe that our methods and results are help- ful in the study of optic radiation fiber tract information.展开更多
It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon O...It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.展开更多
基金supported by the National Natural Science Foundation of China(6087403160740430664)
文摘Fuzzy c-means （FCM） algorithm is one of the most popular methods for image segmentation. However, the standard FCM algorithm is sensitive to noise because of not taking into account the spatial information in the image. An improved FCM algorithm is proposed to improve the antinoise performance of FCM algorithm. The new algorithm is formulated by incorporating the spatial neighborhood information into the membership function for clustering. The distribution statistics of the neighborhood pixels and the prior probability are used to form a new membership func- tion. It is not only effective to remove the noise spots but also can reduce the misclassified pixels. Experimental results indicate that the proposed algorithm is more accurate and robust to noise than the standard FCM algorithm.
基金We acknowledge the support of the Australian Research Council for the Center of Excellence for Coherent X-ray Science(CE0561787).
文摘A wide range of techniques has been developed to image biological samples at high spatial and temporal resolution.In this paper,we report recent results from deep-UV confocal fAuorescence microscopy to image inherent emission from fuorophores such as tryptophan,and structured ilumination microscopy(SIM)of biological materials.One motivation for developing deep-UV fhuorescence imaging and SIM is to provide methods to complement our measurements in the emerging field of X-ray coherent diffractive imaging.
文摘To attain the volumetric information of the optic radiation in normal human brains, we per- formed diffusion tensor imaging examination in 13 healthy volunteers. Simultaneously, we used a brain normalization method to reduce individual brain variation and increase the accuracy of volumetric information analysis. In addition, tractography-based group mapping method was also used to investigate the probability and distribution of the optic radiation pathways. Our results showed that the measured optic radiation fiber tract volume was a range of about 0.16% and that the fractional anisotropy value was about 0.53. Moreover, the optic radiation probability fiber pathway that was determined with diffusion tensor tractography-based group mapping was able to detect the location relatively accurately. We believe that our methods and results are help- ful in the study of optic radiation fiber tract information.
基金support from the Strategic Pilot Science and Technology project of the Chinese Academy of Sciences(Grant No.XDA05040200)the National Natural Science Foundation of China(Grant No.41275040)
文摘It has been several years since the Greenhouse Gases Observing Satellite （GOSAT） began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager （TANSO-CAI） cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer （FTS） observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager （ASI） over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.
