The Experts below are selected from a list of 24324 Experts worldwide ranked by ideXlab platform

Hui Gao - One of the best experts on this subject based on the ideXlab platform.

  • Cadmium uptake in radish (Raphanus sativus L.) and surficial contamination: implications for food safety and local soil management
    Journal of Soils and Sediments, 2019
    Co-Authors: Genyan Xu, Roger Brewer, Jing Song, Sha Zhang, Hui Gao
    Abstract:

    PurposeSoil management strategies for agricultural lands contaminated with potentially toxic trace elements, especially cadmium (Cd), are still inadequate and require a precise identification of soils that are not s afe for growing crops. Key soil variables need to be identified to connect soil safety with food safety by reliable models.Materials and methodsSoil variables that affect concentrations of metals in different portions of radish, Raphanus sativus L., were examined as part of a greenhouse experiment. 0.01 M di-sodium-di-hydroxy-ethylenediamine-tretra-acetic acid (Na2H2EDTA) solution was used in a strong rinsing experiment. Cd soil-radish relationships were derived by different modeling approaches and were used to develop local risk screening values for Cd in soil.Results and discussionThe current lab washing procedures readily remove Surface Cd adherence but are not adequate to remove Surface-deposited lead (Pb), thus overestimating bioaccumulation in plants by mean 111%. Shoot and root tissue Cd concentration in fresh weight basis do not present a significant difference and can be precisely predicted by regression models using different Cd pools and soil pH. Preferably a Polynomial Surface model can be used in developing local rick screening values that yield concentrations of Cd in radish at or below the Chinese food quality standard of 0.1 mg kg−1 (fresh weight).ConclusionsThe bioaccumulation of Cd in radish depends on the Cd bioavailability in soil. But for Pb, surficial particle contamination masks the realistic bioaccumulation. We also demonstrated the usefulness of the Polynomial Surface model to develop local soil protection guidelines that are helpful to local farmers for proper soil management and avoidance of Cd exceedance in food.

  • cadmium uptake in radish raphanus sativus l and surficial contamination implications for food safety and local soil management
    Journal of Soils and Sediments, 2019
    Co-Authors: Sha Zhang, Roger Brewer, Jing Song, Hui Gao
    Abstract:

    Soil management strategies for agricultural lands contaminated with potentially toxic trace elements, especially cadmium (Cd), are still inadequate and require a precise identification of soils that are not s afe for growing crops. Key soil variables need to be identified to connect soil safety with food safety by reliable models. Soil variables that affect concentrations of metals in different portions of radish, Raphanus sativus L., were examined as part of a greenhouse experiment. 0.01 M di-sodium-di-hydroxy-ethylenediamine-tretra-acetic acid (Na2H2EDTA) solution was used in a strong rinsing experiment. Cd soil-radish relationships were derived by different modeling approaches and were used to develop local risk screening values for Cd in soil. The current lab washing procedures readily remove Surface Cd adherence but are not adequate to remove Surface-deposited lead (Pb), thus overestimating bioaccumulation in plants by mean 111%. Shoot and root tissue Cd concentration in fresh weight basis do not present a significant difference and can be precisely predicted by regression models using different Cd pools and soil pH. Preferably a Polynomial Surface model can be used in developing local rick screening values that yield concentrations of Cd in radish at or below the Chinese food quality standard of 0.1 mg kg−1 (fresh weight). The bioaccumulation of Cd in radish depends on the Cd bioavailability in soil. But for Pb, surficial particle contamination masks the realistic bioaccumulation. We also demonstrated the usefulness of the Polynomial Surface model to develop local soil protection guidelines that are helpful to local farmers for proper soil management and avoidance of Cd exceedance in food.

Chung-ming Chen - One of the best experts on this subject based on the ideXlab platform.

  • intensity inhomogeneity correction for the breast sonogram constrained fuzzy cell based bipartitioning and Polynomial Surface modeling
    Medical Physics, 2010
    Co-Authors: Chia-yen Lee, Yi-hong Chou, Chiun-sheng Huang, Yeun-chung Chang, Chui-mei Tiu, Chung-ming Chen
    Abstract:

    Purpose: To develop an intensity inhomogeneity algorithm for breast sonograms in order to assist visual identification and automatic delineation of lesion boundaries. Methods: The proposed algorithm was composed of two essential ideas. One was decomposing the region of interest (ROI) into foreground and background regions by a cell-based segmentation algorithm, called constrained fuzzy cell-based bipartition-EM (CFCB-EM) algorithm. The CFCB-EM algorithm deformed the contour in a fuzzy cell-based deformation fashion with the cell structures derived by the fuzzy cell competition (FCC) algorithm as the deformation unit and the boundary estimated by the normalized cut (NC) algorithm as the reference contour. The other was modeling the intensity inhomogeneity in an ROI as a spatially variant normal distribution with a constant variance and spatially variant means, which formed a Polynomial Surface of order n . The proposed algorithm was formulated as a nested EM algorithm comprising the outer-layer EM algorithm, i.e., the intensity inhomogeneity correction-EM (IIC-EM) algorithm, and the inner-layer EM algorithm, i.e., the CFCB-EM algorithm. The E step of the IIC-EM algorithm was to provide a reasonably good bipartition separating the ROI into foreground and background regions, which included three major component algorithms, namely, the FCC, the NC, and the CFCB-EM. The M step of the IIC-EM algorithm was to estimate and correct the intensity inhomogeneity field by least-squared fitting the intensity inhomogeneity to an n th order Polynomial Surface. Forty-nine breast sonograms with intensity inhomogeneity, each from a different subject, were randomly selected for performance analysis. Three assessments were carried out to evaluate the effectiveness of the proposed algorithm. Results: Based on the visual evaluation of two experienced radiologists, in the first assessment, 46 out of 49 breast lesions were considered to have better contrasts on the inhomogeneity-corrected images by both radiologists. The interrater reliability for the radiologists was found to be kappa = 0.479 ( p = 0.001 ) . In the second assessment, the mean gradients of the low-gradient boundary points before and after correction of the intensity inhomogeneity were compared by the paired t-test, yielding a p -value of 0.000, which suggested the proposed intensity inhomogeneity algorithm may enhance the mean gradient of the low-gradient boundary points. By using the paired t-test, the third assessment further showed that the Chan and Vese level set method could derive a much better lesion boundary on the inhomogeneity-corrected image than on the original image ( p = 0.000 ) . Conclusions: The proposed intensity inhomogeneity correction algorithm could not only augment the visibility of lesion boundary but also improve the segmentation result on a breast sonogram.

  • Intensity inhomogeneity correction for the breast sonogram: Constrained fuzzy cell‐based bipartitioning and Polynomial Surface modeling
    Medical physics, 2010
    Co-Authors: Chia-yen Lee, Yi-hong Chou, Chiun-sheng Huang, Yeun-chung Chang, Chui-mei Tiu, Chung-ming Chen
    Abstract:

    Purpose: To develop an intensity inhomogeneity algorithm for breast sonograms in order to assist visual identification and automatic delineation of lesion boundaries. Methods: The proposed algorithm was composed of two essential ideas. One was decomposing the region of interest (ROI) into foreground and background regions by a cell-based segmentation algorithm, called constrained fuzzy cell-based bipartition-EM (CFCB-EM) algorithm. The CFCB-EM algorithm deformed the contour in a fuzzy cell-based deformation fashion with the cell structures derived by the fuzzy cell competition (FCC) algorithm as the deformation unit and the boundary estimated by the normalized cut (NC) algorithm as the reference contour. The other was modeling the intensity inhomogeneity in an ROI as a spatially variant normal distribution with a constant variance and spatially variant means, which formed a Polynomial Surface of order n . The proposed algorithm was formulated as a nested EM algorithm comprising the outer-layer EM algorithm, i.e., the intensity inhomogeneity correction-EM (IIC-EM) algorithm, and the inner-layer EM algorithm, i.e., the CFCB-EM algorithm. The E step of the IIC-EM algorithm was to provide a reasonably good bipartition separating the ROI into foreground and background regions, which included three major component algorithms, namely, the FCC, the NC, and the CFCB-EM. The M step of the IIC-EM algorithm was to estimate and correct the intensity inhomogeneity field by least-squared fitting the intensity inhomogeneity to an n th order Polynomial Surface. Forty-nine breast sonograms with intensity inhomogeneity, each from a different subject, were randomly selected for performance analysis. Three assessments were carried out to evaluate the effectiveness of the proposed algorithm. Results: Based on the visual evaluation of two experienced radiologists, in the first assessment, 46 out of 49 breast lesions were considered to have better contrasts on the inhomogeneity-corrected images by both radiologists. The interrater reliability for the radiologists was found to be kappa = 0.479 ( p = 0.001 ) . In the second assessment, the mean gradients of the low-gradient boundary points before and after correction of the intensity inhomogeneity were compared by the paired t-test, yielding a p -value of 0.000, which suggested the proposed intensity inhomogeneity algorithm may enhance the mean gradient of the low-gradient boundary points. By using the paired t-test, the third assessment further showed that the Chan and Vese level set method could derive a much better lesion boundary on the inhomogeneity-corrected image than on the original image ( p = 0.000 ) . Conclusions: The proposed intensity inhomogeneity correction algorithm could not only augment the visibility of lesion boundary but also improve the segmentation result on a breast sonogram.

Chia-yen Lee - One of the best experts on this subject based on the ideXlab platform.

  • intensity inhomogeneity correction for the breast sonogram constrained fuzzy cell based bipartitioning and Polynomial Surface modeling
    Medical Physics, 2010
    Co-Authors: Chia-yen Lee, Yi-hong Chou, Chiun-sheng Huang, Yeun-chung Chang, Chui-mei Tiu, Chung-ming Chen
    Abstract:

    Purpose: To develop an intensity inhomogeneity algorithm for breast sonograms in order to assist visual identification and automatic delineation of lesion boundaries. Methods: The proposed algorithm was composed of two essential ideas. One was decomposing the region of interest (ROI) into foreground and background regions by a cell-based segmentation algorithm, called constrained fuzzy cell-based bipartition-EM (CFCB-EM) algorithm. The CFCB-EM algorithm deformed the contour in a fuzzy cell-based deformation fashion with the cell structures derived by the fuzzy cell competition (FCC) algorithm as the deformation unit and the boundary estimated by the normalized cut (NC) algorithm as the reference contour. The other was modeling the intensity inhomogeneity in an ROI as a spatially variant normal distribution with a constant variance and spatially variant means, which formed a Polynomial Surface of order n . The proposed algorithm was formulated as a nested EM algorithm comprising the outer-layer EM algorithm, i.e., the intensity inhomogeneity correction-EM (IIC-EM) algorithm, and the inner-layer EM algorithm, i.e., the CFCB-EM algorithm. The E step of the IIC-EM algorithm was to provide a reasonably good bipartition separating the ROI into foreground and background regions, which included three major component algorithms, namely, the FCC, the NC, and the CFCB-EM. The M step of the IIC-EM algorithm was to estimate and correct the intensity inhomogeneity field by least-squared fitting the intensity inhomogeneity to an n th order Polynomial Surface. Forty-nine breast sonograms with intensity inhomogeneity, each from a different subject, were randomly selected for performance analysis. Three assessments were carried out to evaluate the effectiveness of the proposed algorithm. Results: Based on the visual evaluation of two experienced radiologists, in the first assessment, 46 out of 49 breast lesions were considered to have better contrasts on the inhomogeneity-corrected images by both radiologists. The interrater reliability for the radiologists was found to be kappa = 0.479 ( p = 0.001 ) . In the second assessment, the mean gradients of the low-gradient boundary points before and after correction of the intensity inhomogeneity were compared by the paired t-test, yielding a p -value of 0.000, which suggested the proposed intensity inhomogeneity algorithm may enhance the mean gradient of the low-gradient boundary points. By using the paired t-test, the third assessment further showed that the Chan and Vese level set method could derive a much better lesion boundary on the inhomogeneity-corrected image than on the original image ( p = 0.000 ) . Conclusions: The proposed intensity inhomogeneity correction algorithm could not only augment the visibility of lesion boundary but also improve the segmentation result on a breast sonogram.

  • Intensity inhomogeneity correction for the breast sonogram: Constrained fuzzy cell‐based bipartitioning and Polynomial Surface modeling
    Medical physics, 2010
    Co-Authors: Chia-yen Lee, Yi-hong Chou, Chiun-sheng Huang, Yeun-chung Chang, Chui-mei Tiu, Chung-ming Chen
    Abstract:

    Purpose: To develop an intensity inhomogeneity algorithm for breast sonograms in order to assist visual identification and automatic delineation of lesion boundaries. Methods: The proposed algorithm was composed of two essential ideas. One was decomposing the region of interest (ROI) into foreground and background regions by a cell-based segmentation algorithm, called constrained fuzzy cell-based bipartition-EM (CFCB-EM) algorithm. The CFCB-EM algorithm deformed the contour in a fuzzy cell-based deformation fashion with the cell structures derived by the fuzzy cell competition (FCC) algorithm as the deformation unit and the boundary estimated by the normalized cut (NC) algorithm as the reference contour. The other was modeling the intensity inhomogeneity in an ROI as a spatially variant normal distribution with a constant variance and spatially variant means, which formed a Polynomial Surface of order n . The proposed algorithm was formulated as a nested EM algorithm comprising the outer-layer EM algorithm, i.e., the intensity inhomogeneity correction-EM (IIC-EM) algorithm, and the inner-layer EM algorithm, i.e., the CFCB-EM algorithm. The E step of the IIC-EM algorithm was to provide a reasonably good bipartition separating the ROI into foreground and background regions, which included three major component algorithms, namely, the FCC, the NC, and the CFCB-EM. The M step of the IIC-EM algorithm was to estimate and correct the intensity inhomogeneity field by least-squared fitting the intensity inhomogeneity to an n th order Polynomial Surface. Forty-nine breast sonograms with intensity inhomogeneity, each from a different subject, were randomly selected for performance analysis. Three assessments were carried out to evaluate the effectiveness of the proposed algorithm. Results: Based on the visual evaluation of two experienced radiologists, in the first assessment, 46 out of 49 breast lesions were considered to have better contrasts on the inhomogeneity-corrected images by both radiologists. The interrater reliability for the radiologists was found to be kappa = 0.479 ( p = 0.001 ) . In the second assessment, the mean gradients of the low-gradient boundary points before and after correction of the intensity inhomogeneity were compared by the paired t-test, yielding a p -value of 0.000, which suggested the proposed intensity inhomogeneity algorithm may enhance the mean gradient of the low-gradient boundary points. By using the paired t-test, the third assessment further showed that the Chan and Vese level set method could derive a much better lesion boundary on the inhomogeneity-corrected image than on the original image ( p = 0.000 ) . Conclusions: The proposed intensity inhomogeneity correction algorithm could not only augment the visibility of lesion boundary but also improve the segmentation result on a breast sonogram.

Jie Zhou - One of the best experts on this subject based on the ideXlab platform.

  • A new method to estimate changes in glacier Surface elevation based on Polynomial fitting of sparse ICESat—GLAS footprints
    Sensors, 2017
    Co-Authors: Tianjin Huang, Massimo Menenti, Jing Lu, Li Jia, Jie Zhou, Guangcheng Hu
    Abstract:

    We present in this paper a Polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS) to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary Polynomial Surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona’nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) can give estimates of glacier thickness change from 2000 to 2008/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008/2009, when using the GLAS data only and the planar fitting method.

  • a new method to estimate changes in glacier Surface elevation based on Polynomial fitting of sparse icesat glas footprints
    Sensors, 2017
    Co-Authors: Tianjin Huang, Massimo Menenti, Li Jia, Jie Zhou
    Abstract:

    We present in this paper a Polynomial fitting method applicable to segments of footprints measured by the Geoscience Laser Altimeter System (GLAS) to estimate glacier thickness change. Our modification makes the method applicable to complex topography, such as a large mountain glacier. After a full analysis of the planar fitting method to characterize errors of estimates due to complex topography, we developed an improved fitting method by adjusting a binary Polynomial Surface to local topography. The improved method and the planar fitting method were tested on the accumulation areas of the Naimona’nyi glacier and Yanong glacier on along-track facets with lengths of 1000 m, 1500 m, 2000 m, and 2500 m, respectively. The results show that the improved method gives more reliable estimates of changes in elevation than planar fitting. The improved method was also tested on Guliya glacier with a large and relatively flat area and the Chasku Muba glacier with very complex topography. The results in these test sites demonstrate that the improved method can give estimates of glacier thickness change on glaciers with a large area and a complex topography. Additionally, the improved method based on GLAS Data and Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) can give estimates of glacier thickness change from 2000 to 2008/2009, since it takes the 2000 SRTM-DEM as a reference, which is a longer period than 2004 to 2008/2009, when using the GLAS data only and the planar fitting method.

Sha Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Cadmium uptake in radish (Raphanus sativus L.) and surficial contamination: implications for food safety and local soil management
    Journal of Soils and Sediments, 2019
    Co-Authors: Genyan Xu, Roger Brewer, Jing Song, Sha Zhang, Hui Gao
    Abstract:

    PurposeSoil management strategies for agricultural lands contaminated with potentially toxic trace elements, especially cadmium (Cd), are still inadequate and require a precise identification of soils that are not s afe for growing crops. Key soil variables need to be identified to connect soil safety with food safety by reliable models.Materials and methodsSoil variables that affect concentrations of metals in different portions of radish, Raphanus sativus L., were examined as part of a greenhouse experiment. 0.01 M di-sodium-di-hydroxy-ethylenediamine-tretra-acetic acid (Na2H2EDTA) solution was used in a strong rinsing experiment. Cd soil-radish relationships were derived by different modeling approaches and were used to develop local risk screening values for Cd in soil.Results and discussionThe current lab washing procedures readily remove Surface Cd adherence but are not adequate to remove Surface-deposited lead (Pb), thus overestimating bioaccumulation in plants by mean 111%. Shoot and root tissue Cd concentration in fresh weight basis do not present a significant difference and can be precisely predicted by regression models using different Cd pools and soil pH. Preferably a Polynomial Surface model can be used in developing local rick screening values that yield concentrations of Cd in radish at or below the Chinese food quality standard of 0.1 mg kg−1 (fresh weight).ConclusionsThe bioaccumulation of Cd in radish depends on the Cd bioavailability in soil. But for Pb, surficial particle contamination masks the realistic bioaccumulation. We also demonstrated the usefulness of the Polynomial Surface model to develop local soil protection guidelines that are helpful to local farmers for proper soil management and avoidance of Cd exceedance in food.

  • cadmium uptake in radish raphanus sativus l and surficial contamination implications for food safety and local soil management
    Journal of Soils and Sediments, 2019
    Co-Authors: Sha Zhang, Roger Brewer, Jing Song, Hui Gao
    Abstract:

    Soil management strategies for agricultural lands contaminated with potentially toxic trace elements, especially cadmium (Cd), are still inadequate and require a precise identification of soils that are not s afe for growing crops. Key soil variables need to be identified to connect soil safety with food safety by reliable models. Soil variables that affect concentrations of metals in different portions of radish, Raphanus sativus L., were examined as part of a greenhouse experiment. 0.01 M di-sodium-di-hydroxy-ethylenediamine-tretra-acetic acid (Na2H2EDTA) solution was used in a strong rinsing experiment. Cd soil-radish relationships were derived by different modeling approaches and were used to develop local risk screening values for Cd in soil. The current lab washing procedures readily remove Surface Cd adherence but are not adequate to remove Surface-deposited lead (Pb), thus overestimating bioaccumulation in plants by mean 111%. Shoot and root tissue Cd concentration in fresh weight basis do not present a significant difference and can be precisely predicted by regression models using different Cd pools and soil pH. Preferably a Polynomial Surface model can be used in developing local rick screening values that yield concentrations of Cd in radish at or below the Chinese food quality standard of 0.1 mg kg−1 (fresh weight). The bioaccumulation of Cd in radish depends on the Cd bioavailability in soil. But for Pb, surficial particle contamination masks the realistic bioaccumulation. We also demonstrated the usefulness of the Polynomial Surface model to develop local soil protection guidelines that are helpful to local farmers for proper soil management and avoidance of Cd exceedance in food.