Mammography density estimation with automated volumetic breast density measurement
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Ko, Su Yeon; Kim, Eun Kyung; Kim, Min Jung; Moon, Hee Jung [Dept. of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul (Korea, Republic of)
2014-06-15
To compare automated volumetric breast density measurement (VBDM) with radiologists' evaluations based on the Breast Imaging Reporting and Data System (BI-RADS), and to identify the factors associated with technical failure of VBDM. In this study, 1129 women aged 19-82 years who underwent mammography from December 2011 to January 2012 were included. Breast density evaluations by radiologists based on BI-RADS and by VBDM (Volpara Version 1.5.1) were compared. The agreement in interpreting breast density between radiologists and VBDM was determined based on four density grades (D1, D2, D3, and D4) and a binary classification of fatty (D1-2) vs. dense (D3-4) breast using kappa statistics. The association between technical failure of VBDM and patient age, total breast volume, fibroglandular tissue volume, history of partial mastectomy, the frequency of mass > 3 cm, and breast density was analyzed. The agreement between breast density evaluations by radiologists and VBDM was fair (k value = 0.26) when the four density grades (D1/D2/D3/D4) were used and moderate (k value = 0.47) for the binary classification (D1-2/D3-4). Twenty-seven women (2.4%) showed failure of VBDM. Small total breast volume, history of partial mastectomy, and high breast density were significantly associated with technical failure of VBDM (p 0.001 to 0.015). There is fair or moderate agreement in breast density evaluation between radiologists and VBDM. Technical failure of VBDM may be related to small total breast volume, a history of partial mastectomy, and high breast density.
Automated volumetric breast density estimation: A comparison with visual assessment
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Aim: To compare automated volumetric breast density (VBD) measurement with visual assessment according to Breast Imaging Reporting and Data System (BI-RADS), and to determine the factors influencing the agreement between them. Materials and methods: One hundred and ninety-three consecutive screening mammograms reported as negative were included in the study. Three radiologists assigned qualitative BI-RADS density categories to the mammograms. An automated volumetric breast-density method was used to measure VBD (% breast density) and density grade (VDG). Each case was classified into an agreement or disagreement group according to the comparison between visual assessment and VDG. The correlation between visual assessment and VDG was obtained. Various physical factors were compared between the two groups. Results: Agreement between visual assessment by the radiologists and VDG was good (ICC value = 0.757). VBD showed a highly significant positive correlation with visual assessment (Spearman's ρ = 0.754, p < 0.001). VBD and the x-ray tube target was significantly different between the agreement group and the disagreement groups (p = 0.02 and 0.04, respectively). Conclusion: Automated VBD is a reliable objective method to measure breast density. The agreement between VDG and visual assessment by radiologist might be influenced by physical factors
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Purpose: Breast density has been found to be a potential indicator for breast cancer risk. The estimation of breast density can be seen as a segmentation problem on fibroglandular tissues from a breast magnetic resonance image. The classic moment preserving is a thresholding method, which can be applied to determine an appropriate threshold value for fibroglandular tissue segmentation. Methods: This study proposed an adaptive moment preserving method, which combines the classic moment preserving and a thresholding adjustment method. The breast MR images are firstly performed to extract the fibroglandular tissue from the breast tissue. The next step is to obtain the areas of the fibroglandular tissue and the whole breast tissue. Finally, breast density can be estimated for the given breast. Results: The Friedman test shows that the qualities of segmentation are insignificant with p < 0.000 and Friedman chi-squared = 1116.12. The Friedman test shows that there would be significant differences in the sum of the ranks of at least one segmentation method. Average ranks indicate that the performance of the four methods is ranked as adaptive moment preserving, fuzzy c-means, moment preserving, and Kapur's method in order. Among the four methods, adaptive moment preserving also achieves the minimum values of MAE and RMSE with 9.2 and 12. Conclusion: This study has verified that the proposed adaptive moment preserving can identify and segment the fibroglandular tissues from the 2D breast MR images and estimate the degrees of breast density.
Chen, Biao; Ruth, Chris; Jing, Zhenxue; Ren, Baorui; Smith, Andrew; Kshirsagar, Ashwini
2014-03-01
Breast density has been identified to be a risk factor of developing breast cancer and an indicator of lesion diagnostic obstruction due to masking effect. Volumetric density measurement evaluates fibro-glandular volume, breast volume, and breast volume density measures that have potential advantages over area density measurement in risk assessment. One class of volume density computing methods is based on the finding of the relative fibro-glandular tissue attenuation with regards to the reference fat tissue, and the estimation of the effective x-ray tissue attenuation differences between the fibro-glandular and fat tissue is key to volumetric breast density computing. We have modeled the effective attenuation difference as a function of actual x-ray skin entrance spectrum, breast thickness, fibro-glandular tissue thickness distribution, and detector efficiency. Compared to other approaches, our method has threefold advantages: (1) avoids the system calibration-based creation of effective attenuation differences which may introduce tedious calibrations for each imaging system and may not reflect the spectrum change and scatter induced overestimation or underestimation of breast density; (2) obtains the system specific separate and differential attenuation values of fibroglandular and fat for each mammographic image; and (3) further reduces the impact of breast thickness accuracy to volumetric breast density. A quantitative breast volume phantom with a set of equivalent fibro-glandular thicknesses has been used to evaluate the volume breast density measurement with the proposed method. The experimental results have shown that the method has significantly improved the accuracy of estimating breast density.
Effect of compression paddle tilt correction on volumetric breast density estimation
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For the acquisition of a mammogram, a breast is compressed between a compression paddle and a support table. When compression is applied with a flexible compression paddle, the upper plate may be tilted, which results in variation in breast thickness from the chest wall to the breast margin. Paddle tilt has been recognized as a major problem in volumetric breast density estimation methods. In previous work, we developed a fully automatic method to correct the image for the effect of compression paddle tilt. In this study, we investigated in three experiments the effect of paddle tilt and its correction on volumetric breast density estimation. Results showed that paddle tilt considerably affected accuracy of volumetric breast density estimation, but that effect could be reduced by tilt correction. By applying tilt correction, a significant increase in correspondence between mammographic density estimates and measurements on MRI was established. We argue that in volumetric breast density estimation, tilt correction is both feasible and essential when mammographic images are acquired with a flexible compression paddle. (paper)
Robust estimation of mammographic breast density: a patient-based approach
Heese, Harald S.; Erhard, Klaus; Gooßen, Andre; Bulow, Thomas
2012-02-01
Breast density has become an established risk indicator for developing breast cancer. Current clinical practice reflects this by grading mammograms patient-wise as entirely fat, scattered fibroglandular, heterogeneously dense, or extremely dense based on visual perception. Existing (semi-) automated methods work on a per-image basis and mimic clinical practice by calculating an area fraction of fibroglandular tissue (mammographic percent density). We suggest a method that follows clinical practice more strictly by segmenting the fibroglandular tissue portion directly from the joint data of all four available mammographic views (cranio-caudal and medio-lateral oblique, left and right), and by subsequently calculating a consistently patient-based mammographic percent density estimate. In particular, each mammographic view is first processed separately to determine a region of interest (ROI) for segmentation into fibroglandular and adipose tissue. ROI determination includes breast outline detection via edge-based methods, peripheral tissue suppression via geometric breast height modeling, and - for medio-lateral oblique views only - pectoral muscle outline detection based on optimizing a three-parameter analytic curve with respect to local appearance. Intensity harmonization based on separately acquired calibration data is performed with respect to compression height and tube voltage to facilitate joint segmentation of available mammographic views. A Gaussian mixture model (GMM) on the joint histogram data with a posteriori calibration guided plausibility correction is finally employed for tissue separation. The proposed method was tested on patient data from 82 subjects. Results show excellent correlation (r = 0.86) to radiologist's grading with deviations ranging between -28%, (q = 0.025) and +16%, (q = 0.975).
Chen, Lin; Ray, Shonket; Keller, Brad M; Pertuz, Said; McDonald, Elizabeth S; Conant, Emily F; Kontos, Despina
2016-09-01
Purpose To investigate the impact of radiation dose on breast density estimation in digital mammography. Materials and Methods With institutional review board approval and Health Insurance Portability and Accountability Act compliance under waiver of consent, a cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was retrospectively analyzed. All patients underwent breast screening with a combination of dose protocols, including standard full-field digital mammography, low-dose digital mammography, and digital breast tomosynthesis. A total of 5832 images from 486 women were analyzed with previously validated, fully automated software for quantitative estimation of density. Clinical Breast Imaging Reporting and Data System (BI-RADS) density assessment results were also available from the trial reports. The influence of image acquisition radiation dose on quantitative breast density estimation was investigated with analysis of variance and linear regression. Pairwise comparisons of density estimations at different dose levels were performed with Student t test. Agreement of estimation was evaluated with quartile-weighted Cohen kappa values and Bland-Altman limits of agreement. Results Radiation dose of image acquisition did not significantly affect quantitative density measurements (analysis of variance, P = .37 to P = .75), with percent density demonstrating a high overall correlation between protocols (r = 0.88-0.95; weighted κ = 0.83-0.90). However, differences in breast percent density (1.04% and 3.84%, P mammography are not substantially affected by variations in radiation dose; thus, the use of low-dose techniques for the purpose of density estimation may be feasible. (©) RSNA, 2016 Online supplemental material is available for this article. PMID:27002418
Breast Density and Your Breast Mammogram Report
Breast Density and Your Mammogram Report Regular mammograms are the best way to find breast cancer early. But if ... But in some women, there’s little change. Breast density is very common, and is not abnormal. How ...
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Purpose: High breast density, as measured by mammography, is associated with increased breast cancer risk, but standard methods of assessment have limitations including 2D representation of breast tissue, distortion due to breast compression, and use of ionizing radiation. Ultrasound tomography (UST) is a novel imaging method that averts these limitations and uses sound speed measures rather than x-ray imaging to estimate breast density. The authors evaluated the reproducibility of measures of speed of sound and changes in this parameter using UST. Methods: One experienced and five newly trained raters measured sound speed in serial UST scans for 22 women (two scans per person) to assess inter-rater reliability. Intrarater reliability was assessed for four raters. A random effects model was used to calculate the percent variation in sound speed and change in sound speed attributable to subject, scan, rater, and repeat reads. The authors estimated the intraclass correlation coefficients (ICCs) for these measures based on data from the authors’ experienced rater. Results: Median (range) time between baseline and follow-up UST scans was five (1–13) months. Contributions of factors to sound speed variance were differences between subjects (86.0%), baseline versus follow-up scans (7.5%), inter-rater evaluations (1.1%), and intrarater reproducibility (∼0%). When evaluating change in sound speed between scans, 2.7% and ∼0% of variation were attributed to inter- and intrarater variation, respectively. For the experienced rater’s repeat reads, agreement for sound speed was excellent (ICC = 93.4%) and for change in sound speed substantial (ICC = 70.4%), indicating very good reproducibility of these measures. Conclusions: UST provided highly reproducible sound speed measurements, which reflect breast density, suggesting that UST has utility in sensitively assessing change in density
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Khodr, Zeina G.; Pfeiffer, Ruth M.; Gierach, Gretchen L., E-mail: GierachG@mail.nih.gov [Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive MSC 9774, Bethesda, Maryland 20892 (United States); Sak, Mark A.; Bey-Knight, Lisa [Karmanos Cancer Institute, Wayne State University, 4100 John R, Detroit, Michigan 48201 (United States); Duric, Nebojsa; Littrup, Peter [Karmanos Cancer Institute, Wayne State University, 4100 John R, Detroit, Michigan 48201 and Delphinus Medical Technologies, 46701 Commerce Center Drive, Plymouth, Michigan 48170 (United States); Ali, Haythem; Vallieres, Patricia [Henry Ford Health System, 2799 W Grand Boulevard, Detroit, Michigan 48202 (United States); Sherman, Mark E. [Division of Cancer Prevention, National Cancer Institute, Department of Health and Human Services, 9609 Medical Center Drive MSC 9774, Bethesda, Maryland 20892 (United States)
2015-10-15
Purpose: High breast density, as measured by mammography, is associated with increased breast cancer risk, but standard methods of assessment have limitations including 2D representation of breast tissue, distortion due to breast compression, and use of ionizing radiation. Ultrasound tomography (UST) is a novel imaging method that averts these limitations and uses sound speed measures rather than x-ray imaging to estimate breast density. The authors evaluated the reproducibility of measures of speed of sound and changes in this parameter using UST. Methods: One experienced and five newly trained raters measured sound speed in serial UST scans for 22 women (two scans per person) to assess inter-rater reliability. Intrarater reliability was assessed for four raters. A random effects model was used to calculate the percent variation in sound speed and change in sound speed attributable to subject, scan, rater, and repeat reads. The authors estimated the intraclass correlation coefficients (ICCs) for these measures based on data from the authors’ experienced rater. Results: Median (range) time between baseline and follow-up UST scans was five (1–13) months. Contributions of factors to sound speed variance were differences between subjects (86.0%), baseline versus follow-up scans (7.5%), inter-rater evaluations (1.1%), and intrarater reproducibility (∼0%). When evaluating change in sound speed between scans, 2.7% and ∼0% of variation were attributed to inter- and intrarater variation, respectively. For the experienced rater’s repeat reads, agreement for sound speed was excellent (ICC = 93.4%) and for change in sound speed substantial (ICC = 70.4%), indicating very good reproducibility of these measures. Conclusions: UST provided highly reproducible sound speed measurements, which reflect breast density, suggesting that UST has utility in sensitively assessing change in density.
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Keller, Brad M.; Nathan, Diane L.; Wang Yan; Zheng Yuanjie; Gee, James C.; Conant, Emily F.; Kontos, Despina [Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States)
2012-08-15
Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., 'FOR PROCESSING') and vendor postprocessed (i.e., 'FOR PRESENTATION'), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely
International Nuclear Information System (INIS)
Purpose: The amount of fibroglandular tissue content in the breast as estimated mammographically, commonly referred to as breast percent density (PD%), is one of the most significant risk factors for developing breast cancer. Approaches to quantify breast density commonly focus on either semiautomated methods or visual assessment, both of which are highly subjective. Furthermore, most studies published to date investigating computer-aided assessment of breast PD% have been performed using digitized screen-film mammograms, while digital mammography is increasingly replacing screen-film mammography in breast cancer screening protocols. Digital mammography imaging generates two types of images for analysis, raw (i.e., “FOR PROCESSING”) and vendor postprocessed (i.e., “FOR PRESENTATION”), of which postprocessed images are commonly used in clinical practice. Development of an algorithm which effectively estimates breast PD% in both raw and postprocessed digital mammography images would be beneficial in terms of direct clinical application and retrospective analysis. Methods: This work proposes a new algorithm for fully automated quantification of breast PD% based on adaptive multiclass fuzzy c-means (FCM) clustering and support vector machine (SVM) classification, optimized for the imaging characteristics of both raw and processed digital mammography images as well as for individual patient and image characteristics. Our algorithm first delineates the breast region within the mammogram via an automated thresholding scheme to identify background air followed by a straight line Hough transform to extract the pectoral muscle region. The algorithm then applies adaptive FCM clustering based on an optimal number of clusters derived from image properties of the specific mammogram to subdivide the breast into regions of similar gray-level intensity. Finally, a SVM classifier is trained to identify which clusters within the breast tissue are likely fibroglandular, which
Keller, Brad M.; Nathan, Diane L.; Conant, Emily F.; Kontos, Despina
2012-03-01
Breast percent density (PD%), as measured mammographically, is one of the strongest known risk factors for breast cancer. While the majority of studies to date have focused on PD% assessment from digitized film mammograms, digital mammography (DM) is becoming increasingly common, and allows for direct PD% assessment at the time of imaging. This work investigates the accuracy of a generalized linear model-based (GLM) estimation of PD% from raw and postprocessed digital mammograms, utilizing image acquisition physics, patient characteristics and gray-level intensity features of the specific image. The model is trained in a leave-one-woman-out fashion on a series of 81 cases for which bilateral, mediolateral-oblique DM images were available in both raw and post-processed format. Baseline continuous and categorical density estimates were provided by a trained breast-imaging radiologist. Regression analysis is performed and Pearson's correlation, r, and Cohen's kappa, κ, are computed. The GLM PD% estimation model performed well on both processed (r=0.89, pbreast PD% could allow for a reproducible estimation of breast density, providing a rapid risk assessment tool for clinical practice.
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Purpose: Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment. Methods: In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandular tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's pairedt-test, and Dice's similarity coefficients (DSC). Results: The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers’ manual segmentation, the proposed FCM-Atlas method achieves a correlation ofr = 0
Automatic breast density classification using neural network
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According to studies, the risk of breast cancer directly associated with breast density. Many researches are done on automatic diagnosis of breast density using mammography. In the current study, artifacts of mammograms are removed by using image processing techniques and by using the method presented in this study, including the diagnosis of points of the pectoral muscle edges and estimating them using regression techniques, pectoral muscle is detected with high accuracy in mammography and breast tissue is fully automatically extracted. In order to classify mammography images into three categories: Fatty, Glandular, Dense, a feature based on difference of gray-levels of hard tissue and soft tissue in mammograms has been used addition to the statistical features and a neural network classifier with a hidden layer. Image database used in this research is the mini-MIAS database and the maximum accuracy of system in classifying images has been reported 97.66% with 8 hidden layers in neural network
Association between mammographic density and basal-like and luminal A breast cancer subtypes
Razzaghi, Hilda; Troester, Melissa A.; Gierach, Gretchen L.; Olshan, Andrew F.; Yankaskas, Bonnie C.; Millikan, Robert C.
2013-01-01
Introduction Mammographic density is a strong risk factor for breast cancer overall, but few studies have examined the association between mammographic density and specific subtypes of breast cancer, especially aggressive basal-like breast cancers. Because basal-like breast cancers are less frequently screen-detected, it is important to understand how mammographic density relates to risk of basal-like breast cancer. Methods We estimated associations between mammographic density and breast can...
Postmortem validation of breast density using dual-energy mammography
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Molloi, Sabee, E-mail: symolloi@uci.edu; Ducote, Justin L.; Ding, Huanjun; Feig, Stephen A. [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)
2014-08-15
Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.
Postmortem validation of breast density using dual-energy mammography
International Nuclear Information System (INIS)
Purpose: Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. Methods: Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. Results: Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. Conclusions: The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer
Breast density and mode of detection in relation to breast cancer specific survival: a cohort study
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The aim of this study was to examine breast density in relation to breast cancer specific survival and to assess if this potential association was modified by mode of detection. An additional aim was to study whether the established association between mode of detection and survival is modified by breast density. The study included 619 cases from a prospective cohort, The Malmö Diet and Cancer Study. Breast density estimated qualitatively, was analyzed in relation to breast cancer death, in non-symptomatic and symptomatic women, using Cox regression calculating hazard ratios (HR) with 95% confidence intervals. Adjustments were made in several steps for; diagnostic age, tumour size, axillary lymph node involvement, grade, hormone receptor status, body mass index (baseline), diagnostic period, use of hormone replacement therapy at diagnosis and mode of detection. Detection mode in relation to survival was analyzed stratified for breast density. Differences in HR following different adjustments were analyzed by Freedmans%. After adjustment for age and other prognostic factors, women with dense, as compared to fatty breasts, had an increased risk of breast cancer death, HR 2.56:1.07-6.11, with a statistically significant trend over density categories, p = 0.04. In the stratified analysis, the effect was less pronounced in non-symptomatic women, HR 2.04:0.49-8.49 as compared to symptomatic, HR 3.40:1.06-10.90. In the unadjusted model, symptomatic women had a higher risk of breast cancer death, regardless of breast density. Analyzed by Freedmans%, age, tumour size, lymph nodes, grade, diagnostic period, ER and PgR explained 55.5% of the observed differences in mortality between non-symptomatic and symptomatic cases. Additional adjustment for breast density caused only a minor change. High breast density at diagnosis may be associated with decreased breast cancer survival. This association appears to be stronger in women with symptomatic cancers but breast density could
Breast density characterization using texton distributions.
Petroudi, Styliani; Brady, Michael
2011-01-01
Breast density has been shown to be one of the most significant risks for developing breast cancer, with women with dense breasts at four to six times higher risk. The Breast Imaging Reporting and Data System (BI-RADS) has a four class classification scheme that describes the different breast densities. However, there is great inter and intra observer variability among clinicians in reporting a mammogram's density class. This work presents a novel texture classification method and its application for the development of a completely automated breast density classification system. The new method represents the mammogram using textons, which can be thought of as the building blocks of texture under the operational definition of Leung and Malik as clustered filter responses. The new proposed method characterizes the mammographic appearance of the different density patterns by evaluating the texton spatial dependence matrix (TDSM) in the breast region's corresponding texton map. The TSDM is a texture model that captures both statistical and structural texture characteristics. The normalized TSDM matrices are evaluated for mammograms from the different density classes and corresponding texture models are established. Classification is achieved using a chi-square distance measure. The fully automated TSDM breast density classification method is quantitatively evaluated on mammograms from all density classes from the Oxford Mammogram Database. The incorporation of texton spatial dependencies allows for classification accuracy reaching over 82%. The breast density classification accuracy is better using texton TSDM compared to simple texton histograms. PMID:22255462
Quantitative assessment of breast density: comparison of different methods
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Objective: To Compare different methods of quantitative breast density measurement. Methods: The study included sixty patients who underwent both mammography and breast MRI. The breast density was computed automatically on digital mammograms with R2 workstation, Two experienced radiologists read the mammograms and assessed the breast density with Wolfe and ACR classification respectively. Fuzzy C-means clustering algorithm (FCM) was used to assess breast density on MRI. Each assessment method was repeated after 2 weeks. Spearman and Pearson correlations of inter- and intrareader and intermodality were computed for density estimates. Results: Inter- and intrareader correlation of Wolfe classification were 0.74 and 0.65, and they were 0.74 and 0.82 for ACR classification respectively. Correlation between Wolfe and ACR classification was 0.77. High interreader correlation of 0.98 and intrareader correlation of 0.96 was observed with MR FCM measurement. And the correlation between digital mammograms and MRI was high in the assessment of breast density (r=0.81, P<0.01). Conclusion: High correlation of breast density estimates on digital mammograms and MRI FCM suggested the former could be used as a simple and accurate method. (authors)
The Estimation of Conditional Densities
Xiaohong Chen; Oliver Linton; Robinson, Peter M.
2001-01-01
We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio of joint and marginal density estimates. We point out the different implications of leading choices of bandwidths in numerator and denominator for the ability of the estimate to integrate to one and to have finite moments. Again bearing in mind different bandwidth possibilities, we discuss asympt...
A Review of Segmentation of Mammographic Images Based on Breast Density
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Anusree Mohan
2015-03-01
Full Text Available Breast cancer is one of the leading causes of fatality in women. Mammogram is the effectual modality for early detection of breast cancer. Increased mammographic breast density is a moderate independent risk factor for breast cancer, Radiologists have estimated breast density using four broad categories (BI-RADS swearing on visual assessment of mammograms. The aim of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appears bright on mammograms and is described as breast density. Most of the studies are focused on the classification methods for glandular tissue detection. Others highlighted on the segmentation methods for fibroglandular tissue, while few researchers performed segmentation of the breast anatomical regions based on density. There have also been works on the segmentation of other specific parts of breast regions such as either detection of nipple position, skin-air interface or pectoral muscles. The problems on the evaluation performance of the segmentation results in relation to ground truth are also discussed in this paper.
Optimization of Barron density estimates
Czech Academy of Sciences Publication Activity Database
Vajda, Igor; van der Meulen, E. C.
2001-01-01
Roč. 47, č. 5 (2001), s. 1867-1883. ISSN 0018-9448 R&D Projects: GA ČR GA102/99/1137 Grant ostatní: Copernicus(XE) 579 Institutional research plan: AV0Z1075907 Keywords : Barron estimator * chi-square criterion * density estimation Subject RIV: BD - Theory of Information Impact factor: 2.077, year: 2001
Mueller-Schimpfle, M P; Brandenbusch, V C; Degenhardt, F; Duda, V; Madjar, H; Mundinger, A; Rathmann, R; Hahn, M
2016-04-01
Mammographic breast density correlates with breast cancer risk and also with the number of false-negative calls. In the USA these facts lead to the "Breast Density and Mammography Reporting Act" of 2011. In the case of mammographically dense breasts, the Working Group on Breast Ultrasound in Germany recommends explaining the advantages of adjunct imaging to women, depending on the individual breast cancer risk. Due to the particular structure of German healthcare, quality-assured breast ultrasound would be the first choice. Possible overdiagnosis, costs, potentially increased emotional stress should be addressed. In high familial breast cancer risk, genetic counselling and an intensified early detection program should be performed. PMID:26882482
Variability of breast density assessment in short-term reimaging with digital mammography
Energy Technology Data Exchange (ETDEWEB)
Kim, Won Hwa [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Moon, Woo Kyung, E-mail: moonwk@snu.ac.kr [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Kim, Sun Mi [Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do (Korea, Republic of); Yi, Ann [Department of Radiology, Seoul Metropolitan Government Seoul National University, Boramae Medical Center, Seoul (Korea, Republic of); Chang, Jung Min; Koo, Hye Ryoung; Lee, Su Hyun; Cho, Nariya [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of)
2013-10-01
Objective: To evaluate the variability of breast density assessments in short-term reimaging with digital mammography. Materials and methods: In 186 women, short term (mean interval, 27.6 days) serial digital mammograms including CC and MLO views were obtained without any treatment. Mammographic density assessments were performed by three blinded radiologists for Breast Imaging Report and Data System (BI-RADS, grades 1–4) and visual percentage density (PD) estimation, and by one radiologist for computer-aided PD estimation. The variability of assessments was analyzed according to the age, breast density, and mammography types by multivariate logistic regression. Results: In BI-RADS assessments, 29% (161 of 558) of breast density categories were assessed differently after short-term reimaging and the mean absolute difference in PD for CC and MLO view was 7.6% and 8.1% for visual assessments, and 7.4% and 6.4% for computer-aided assessments, respectively. Among all computer-aided assessments, 29% (54 of 186) of CC view and 22% (41 of 186) of MLO view assessments had discrepancy over 10% in PD. Younger age (<50), greater breast density (grades 3 and 4), and different mammography types were significantly associated with the variability. Conclusion: Considerable variability in breast density assessments occurred in short-term reimaging with digital mammography, particularly in women with younger age and greater breast density and when examined using different types of mammography.
Variability of breast density assessment in short-term reimaging with digital mammography
International Nuclear Information System (INIS)
Objective: To evaluate the variability of breast density assessments in short-term reimaging with digital mammography. Materials and methods: In 186 women, short term (mean interval, 27.6 days) serial digital mammograms including CC and MLO views were obtained without any treatment. Mammographic density assessments were performed by three blinded radiologists for Breast Imaging Report and Data System (BI-RADS, grades 1–4) and visual percentage density (PD) estimation, and by one radiologist for computer-aided PD estimation. The variability of assessments was analyzed according to the age, breast density, and mammography types by multivariate logistic regression. Results: In BI-RADS assessments, 29% (161 of 558) of breast density categories were assessed differently after short-term reimaging and the mean absolute difference in PD for CC and MLO view was 7.6% and 8.1% for visual assessments, and 7.4% and 6.4% for computer-aided assessments, respectively. Among all computer-aided assessments, 29% (54 of 186) of CC view and 22% (41 of 186) of MLO view assessments had discrepancy over 10% in PD. Younger age (<50), greater breast density (grades 3 and 4), and different mammography types were significantly associated with the variability. Conclusion: Considerable variability in breast density assessments occurred in short-term reimaging with digital mammography, particularly in women with younger age and greater breast density and when examined using different types of mammography
Diffuse optical tomography with structured-light patterns to quantify breast density
Kwong, Jessica; Nouizi, Farouk; Cho, Jaedu; Zheng, Jie; Li, Yifan; Chen, Jeon-hor; Su, Min-Ying; Gulsen, Gultekin
2016-02-01
Breast density is an independent risk factor for breast cancer, where women with denser breasts are more likely to develop cancer. By identifying women at higher risk, healthcare providers can suggest screening at a younger age to effectively diagnose and treat breast cancer in its earlier stages. Clinical risk assessment models currently do not incorporate breast density, despite its strong correlation with breast cancer. Current methods to measure breast density rely on mammography and MRI, both of which may be difficult to use as a routine risk assessment tool. We propose to use diffuse optical tomography with structured-light to measure the dense, fibroglandular (FGT) tissue volume, which has a different chromophore signature than the surrounding adipose tissue. To test the ability of this technique, we performed simulations by creating numerical breast phantoms from segmented breast MR images. We looked at two different cases, one with a centralized FGT distribution and one with a dispersed distribution. As expected, the water and lipid volumes segmented at half-maximum were overestimated for the dispersed case. However, it was noticed that the recovered water and lipid concentrations were lower and higher, respectively, than the centralized case. This information may provide insight into the morphological distribution of the FGT and can be a correction in estimating the breast density.
Quantification of breast density using dual-energy mammography with liquid phantom calibration
International Nuclear Information System (INIS)
Breast density is a widely recognized potential risk factor for breast cancer. However, accurate quantification of breast density is a challenging task in mammography. The current use of plastic breast-equivalent phantoms for calibration provides limited accuracy in dual-energy mammography due to the chemical composition of the phantom. We implemented a breast-equivalent liquid phantom for dual-energy calibration in order to improve the accuracy of breast density measurement. To design these phantoms, three liquid compounds were chosen: water, isopropyl alcohol, and glycerol. Chemical compositions of glandular and adipose tissues, obtained from NIST database, were used as reference materials. Dual-energy signal of the liquid phantom at different breast densities (0% to 100%) and thicknesses (1 to 8 cm) were simulated. Glandular and adipose tissue thicknesses were estimated from a higher order polynomial of the signals. Our results indicated that the linear attenuation coefficients of the breast-equivalent liquid phantoms match those of the target material. Comparison between measured and known breast density data shows a linear correlation with a slope close to 1 and a non-zero intercept of 7%, while plastic phantoms showed a slope of 0.6 and a non-zero intercept of 8%. Breast density results derived from the liquid calibration phantoms showed higher accuracy than those derived from the plastic phantoms for different breast thicknesses and various tube voltages. We performed experimental phantom studies using liquid phantoms and then compared the computed breast density with those obtained using a bovine tissue model. The experimental data and the known values were in good correlation with a slope close to 1 (∼1.1). In conclusion, our results indicate that liquid phantoms are a reliable alternative for calibration in dual-energy mammography and better reproduce the chemical properties of the target material. (paper)
Quantification of breast density using dual-energy mammography with liquid phantom calibration
Lam, Alfonso R.; Ding, Huanjun; Molloi, Sabee
2014-07-01
Breast density is a widely recognized potential risk factor for breast cancer. However, accurate quantification of breast density is a challenging task in mammography. The current use of plastic breast-equivalent phantoms for calibration provides limited accuracy in dual-energy mammography due to the chemical composition of the phantom. We implemented a breast-equivalent liquid phantom for dual-energy calibration in order to improve the accuracy of breast density measurement. To design these phantoms, three liquid compounds were chosen: water, isopropyl alcohol, and glycerol. Chemical compositions of glandular and adipose tissues, obtained from NIST database, were used as reference materials. Dual-energy signal of the liquid phantom at different breast densities (0% to 100%) and thicknesses (1 to 8 cm) were simulated. Glandular and adipose tissue thicknesses were estimated from a higher order polynomial of the signals. Our results indicated that the linear attenuation coefficients of the breast-equivalent liquid phantoms match those of the target material. Comparison between measured and known breast density data shows a linear correlation with a slope close to 1 and a non-zero intercept of 7%, while plastic phantoms showed a slope of 0.6 and a non-zero intercept of 8%. Breast density results derived from the liquid calibration phantoms showed higher accuracy than those derived from the plastic phantoms for different breast thicknesses and various tube voltages. We performed experimental phantom studies using liquid phantoms and then compared the computed breast density with those obtained using a bovine tissue model. The experimental data and the known values were in good correlation with a slope close to 1 (˜1.1). In conclusion, our results indicate that liquid phantoms are a reliable alternative for calibration in dual-energy mammography and better reproduce the chemical properties of the target material.
Mammographic breast density as a biomarker of effects of isoflavones on the female breast
Atkinson, Charlotte; Bingham, Sheila A.
2001-01-01
Isoflavones possess both estrogenic and anti-estrogenic actions, and are hypothesized to protect against breast cancer. However, two intervention studies of markers of proliferation on breast tissue have raised concerns that soy isoflavones may have an estrogenic effect on breast tissue. Increased mammographic breast density is associated with an elevated risk of breast cancer, although the mechanism underlying this relationship has not been explained. Estrogens increase and anti-estrogens de...
Breast Cancer Risk Estimation Using Parenchymal Texture Analysis in Digital Breast Tomosynthesis
International Nuclear Information System (INIS)
Mammographic parenchymal texture has been shown to correlate with genetic markers of developing breast cancer. Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique in which tomographic images of the breast are reconstructed from multiple source projections acquired at different angles of the x-ray tube. Compared to digital mammography (DM), DBT eliminates breast tissue overlap, offering superior parenchymal tissue visualization. We hypothesize that texture analysis in DBT could potentially provide a better assessment of parenchymal texture and ultimately result in more accurate assessment of breast cancer risk. As a first step towards validating this hypothesis, we investigated the association between DBT parenchymal texture and breast percent density (PD), a known breast cancer risk factor, and compared it to DM. Bilateral DBT and DM images from 71 women participating in a breast cancer screening trial were analyzed. Filtered-backprojection was used to reconstruct DBT tomographic planes in 1 mm increments with 0.22 mm in-plane resolution. Corresponding DM images were acquired at 0.1 mm pixel resolution. Retroareolar regions of interest (ROIs) equivalent to 2.5 cm3 were segmented from the DBT images and corresponding 2.5 cm2 ROIs were segmented from the DM images. Breast PD was mammographically estimated using the Cumulus scale. Overall, DBT texture features demonstrated a stronger correlation than DM to PD. The Pearson correlation coefficients for DBT were r = 0.40 (p2 = 0.39) compared to DM (R2 = 0.33). We attribute these observations to the superior parenchymal tissue visualization in DBT. Our study is the first to perform DBT texture analysis in a screening population of women, showing that DBT could potentially provide better breast cancer risk assessment in the future.
Vision 20/20: Mammographic breast density and its clinical applications
International Nuclear Information System (INIS)
Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are “dense” and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believe there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component
Vision 20/20: Mammographic breast density and its clinical applications
Energy Technology Data Exchange (ETDEWEB)
Ng, Kwan-Hoong, E-mail: ngkh@ummc.edu.my; Lau, Susie [Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur (Malaysia)
2015-12-15
Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are “dense” and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believe there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component.
Correlations between female breast density and biochemical markers
Kim, Ji-Hye; Lee, Hae-Kag; Cho, Jae-Hwan; Park, Hyong-Keun; Yang, Han-Jun
2015-01-01
[Purpose] The aim of this study was to identify biochemical markers related to breast density. The study was performed with 200 patients who received mammography and biochemical marker testing between March 1, 2014 to October 1, 2014. [Subjects and Methods] Following the American College of Radiology, Breast Imaging Reporting and Data System (ACR BI-RADS), breast parenchymal pattern density from mammography was categorized into four grades: grade 1, almost entirely fat; grade 2, fibroglandula...
Maskarinec, Gertraud; Morimoto, Yukiko; Laguana, Michelle B; Novotny, Rachel; Leon Guerrero, Rachael T
2016-01-01
Although high mammographic density is one of the strongest predictors of breast cancer risk, X-ray based mammography cannot be performed before the recommended screening age, especially not in adolescents and young women. Therefore, new techniques for breast density measurement are of interest. In this pilot study in Guam and Hawaii, we evaluated a radiation-free, bioimpedance device called Electrical Breast DensitometerTM (EBD; senoSENSE Medical Systems, Inc., Ontario, Canada) for measuring breast density in 95 women aged 31-82 years and 41 girls aged 8-18 years. Percent density (PD) was estimated in the women's most recent mammogram using a computer-assisted method. Correlation coefficients and linear regression were applied for statistical analysis. In adult women, mean EBD and PD values of the left and right breasts were 230±52 and 226±50 Ω and 23.7±15.1 and 24.2±15.2%, respectively. The EBD measurements were inversely correlated with PD (rSpearman=-0.52, passessment of breast cancer risk early in life and in populations without access to mammography. PMID:26838256
International Nuclear Information System (INIS)
Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson'sr, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson'sr increased from 0.86 to 0.92 with the bias field correction
Breast density and outcome of mammography screening: a cohort study
DEFF Research Database (Denmark)
Olsen, A H; Bihrmann, K; Jensen, M-B;
2009-01-01
The purpose of this study was to investigate the effect of breast density on breast cancer (BC) mortality in a mammography screening programme. The cohort included 48 052 women participating in mammography screening in Copenhagen, Denmark, where biennial screening is offered to women aged 50...
DEFF Research Database (Denmark)
Andersen, Zorana Jovanovic; Baker, Jennifer Lyn; Bihrmann, Kristine;
2014-01-01
High breast density, a strong predictor of breast cancer may be determined early in life. Childhood anthropometric factors have been related to breast cancer and breast density, but rarely simultaneously. We examined whether mammographic density (MD) mediates an association of birth weight......, childhood body mass index (BMI), and height with the risk of breast cancer....
Density Estimation Trees in High Energy Physics
Anderlini, Lucio
2015-01-01
Density Estimation Trees can play an important role in exploratory data analysis for multidimensional, multi-modal data models of large samples. I briefly discuss the algorithm, a self-optimization technique based on kernel density estimation, and some applications in High Energy Physics.
Bayesian multivariate mixed-scale density estimation
Canale, Antonio
2011-01-01
Although univariate continuous density estimation has received abundant attention in the Bayesian nonparametrics literature, there is essentially no theory on multivariate mixed scale density estimation. In this article, we consider a general framework to jointly model continuous, count and categorical variables under a nonparametric prior, which is induced through rounding latent variables having an unknown density with respect to Lesbesgue measure. For the proposed class of priors, we provide sufficient conditions for large support, strong consistency and rates of posterior contraction. These conditions, which primarily relate to the prior on the latent variable density and heaviness of the tails for the observed continuous variables, allow one to convert sufficient conditions obtained in the setting of multivariate continuous density estimation to the mixed scale case. We provide new results in the multivariate continuous density estimation case, showing the Kullback-Leibler property and strong consistency...
Brandt, Kathleen R; Scott, Christopher G; Ma, Lin; Mahmoudzadeh, Amir P; Jensen, Matthew R; Whaley, Dana H; Wu, Fang Fang; Malkov, Serghei; Hruska, Carrie B; Norman, Aaron D; Heine, John; Shepherd, John; Pankratz, V Shane; Kerlikowske, Karla; Vachon, Celine M
2016-06-01
Purpose To compare the classification of breast density with two automated methods, Volpara (version 1.5.0; Matakina Technology, Wellington, New Zealand) and Quantra (version 2.0; Hologic, Bedford, Mass), with clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications and to examine associations of these measures with breast cancer risk. Materials and Methods In this study, 1911 patients with breast cancer and 4170 control subjects matched for age, race, examination date, and mammography machine were evaluated. Participants underwent mammography at Mayo Clinic or one of four sites within the San Francisco Mammography Registry between 2006 and 2012 and provided informed consent or a waiver for research, in compliance with HIPAA regulations and institutional review board approval. Digital mammograms were retrieved a mean of 2.1 years (range, 6 months to 6 years) before cancer diagnosis, with the corresponding clinical BI-RADS density classifications, and Volpara and Quantra density estimates were generated. Agreement was assessed with weighted κ statistics among control subjects. Breast cancer associations were evaluated with conditional logistic regression, adjusted for age and body mass index. Odds ratios, C statistics, and 95% confidence intervals (CIs) were estimated. Results Agreement between clinical BI-RADS density classifications and Volpara and Quantra BI-RADS estimates was moderate, with κ values of 0.57 (95% CI: 0.55, 0.59) and 0.46 (95% CI: 0.44, 0.47), respectively. Differences of up to 14% in dense tissue classification were found, with Volpara classifying 51% of women as having dense breasts, Quantra classifying 37%, and clinical BI-RADS assessment used to classify 43%. Clinical and automated measures showed similar breast cancer associations; odds ratios for extremely dense breasts versus scattered fibroglandular densities were 1.8 (95% CI: 1.5, 2.2), 1.9 (95% CI: 1.5, 2.5), and 2.3 (95% CI: 1.9, 2.8) for Volpara, Quantra
Nonparametric Estimation of Risk-Neutral Densities
Grith, Maria; Härdle, Wolfgang Karl; Schienle, Melanie
2010-01-01
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk neutral density. The first estimator is a kernel smoother of the second derivative of call prices, while the second procedure applies kernel type smoothing in the implied volatility domain. In the conceptually different third approach we assume...
ADN* Density log estimation Using Rockcell*
International Nuclear Information System (INIS)
This work is intended to inform on the possibilities of estimating good density data in zones associated with sliding in a reservoir with ADN* tool with or without ADOS in string in cases where repeat sections were not done, possibly due to hole stability or directional concerns. This procedure has been equally used to obtain a better density data in corkscrew holes. Density data (ROBB) was recomputed using neural network in RockCell* to estimate the density over zones of interest. RockCell* is a Schlumberger software that has neural network functionally which can be used to estimate missing logs using the combination of the responses of other log curves and intervals that are not affected by sliding. In this work, an interval was selected and within this interval twelve litho zones were defined using the unsupervised neural network. From this a training set was selected based on intervals of very good log responses outside the sliding zones. This training set was used to train and run the neural network for a specific lithostratigraphic interval. The results matched the known good density curve. Then after this, an estimation of the density curve was done using the supervised neural network. The output from this estimation matched very closely in the good portions of the log, thus providing some density measurements in the sliding zone. This methodology provides a scientific solution to missing data during the process of Formation evaluation
Characterization of breast density in women from Lima, Peru
Casado, Fanny L.; Manrique, Susan; Guerrero, Jorge; Pinto, Joseph; Ferrer, Jose; Castaneda, Benjamin
2015-03-01
Data from GLOBOCAN show that around 4,000 Peruvian women are diagnosed with breast cancer every year. From these new cases, the clinical presentation of 36% corresponded to advanced stages (III and IV). Therefore, there is an urgent need to strengthen current screening and early detection strategies. The American College of Radiology (ACR) breast density classification is a risk assessment and quality assurance tool in mammography to standardize and facilitate report to non-radiologists. In our sample of Peruvian women, we found that 45.3% of women have a breast density classified as ACR II, 32.3% as ACR I, 19.7% as ACR III and only 2.7% as ACR IV. Also, premenopausal women are more likely to have breast density types ACR III and IV than postmenopausal women. These results show certain similarity to other populations showing that most breast densities are classified as ACR I and II, but shows a unique distribution when taking into account all four ACR types. Our results are consistent with epidemiological evidence suggesting that the Peruvian population may have a different stratification of risk based on its particular genetic and/or ethnic background. The present work will aid to develop novel strategies for screening and early detection of breast malignancies.
ESTIMATES OF BIOMASS DENSITY FOR TROPICAL FORESTS
An accurate estimation of the biomass density in forests is a necessary step in understanding the global carbon cycle and production of other atmospheric trace gases from biomass burning. n this paper the authors summarize the various approaches that have developed for estimating...
Parametric density estimation by minimizing nonextensive entropy
Davide Ferrari
2008-01-01
In this paper, we consider parametric density estimation based on minimizing the Havrda-Charvat-Tsallis nonextensive entropy. The resulting estimator, called the Maximum Lq-Likelihood estimator (MLqE), is indexed by a single distortion parameter q, which controls the trade-off between bias and variance. The method has two notable special cases. If q tends to 1, the MLqE is the Maximum Likelihood Estimator (MLE). When q = 1=2, the MLqE is a minimum Hellinger distance type of estimator with the...
Directory of Open Access Journals (Sweden)
Hori,Keisuke
2013-08-01
Full Text Available A relatively large number of women in their 40s with high-density breasts, in which it can be difficult to detect lesions, are encountered in mammography cancer screenings in Japan. Here, we retrospectively investigated factors related to breast density. Two hundred women (40-49 years old were examined at the screening center in our hospital. Multivariate analysis showed that factors such as small abdominal circumference, high HDL cholesterol, and no history of childbirth were related to high breast density in women in their 40s undergoing mammography. Other non-mammographic screening methods should be considered in women with abdominal circumferences ＜76cm, HDL-C >53mg/dl, and no history of childbirth, as there is a strong possibility of these women having high-density breasts that can make lesion detection difficult.
Implementation of several mathematical algorithms to breast tissue density classification
Quintana, C.; Redondo, M.; Tirao, G.
2014-02-01
The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.
Classification of breast density in X-ray mammography
Czech Academy of Sciences Publication Activity Database
Remeš, Václav; Haindl, Michal
New York, NY,: IEEE, 2015, s. 1-5. ISBN 978-1-4673-8457-5. [2015 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM). Praha (CZ), 29.10.2015-30.10.2015] R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : Breast cancer * breast density * Mammography * MRF * ACR * BI-RADS Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2016/RO/haindl-0454449.pdf
Estimation of mean glandular dose for mammography of augmented breasts
Beckett, J. R.; Kotre, C. J.
2000-11-01
The standard quantity used to relate breast surface exposure to radiation risk is the mean dose received by the radiation sensitive tissue contained within the female breast, the mean glandular dose (MGD). At present, little is known about the MGD received by women with breast implants as there is no technique available to facilitate its calculation. The present work has involved modification of the conventional method for MGD estimation to make it applicable to women with augmented breasts. The technique was used to calculate MGDs for a cohort of 80 women with breast implants, which were compared with similar data calculated for a total of 1258 non-augmented women. Little difference was found in median MGD at low compressed breast thickness. At high breast thickness, however, the MGDs received by women with augmented breasts were found to be considerably lower than those relating to their non-augmented counterparts.
Estimation of mean glandular dose for mammography of augmented breasts
International Nuclear Information System (INIS)
The standard quantity used to relate breast surface exposure to radiation risk is the mean dose received by the radiation sensitive tissue contained within the female breast, the mean glandular dose (MGD). At present, little is known about the MGD received by women with breast implants as there is no technique available to facilitate its calculation. The present work has involved modification of the conventional method for MGD estimation to make it applicable to women with augmented breasts. The technique was used to calculate MGDs for a cohort of 80 women with breast implants, which were compared with similar data calculated for a total of 1258 non-augmented women. Little difference was found in median MGD at low compressed breast thickness. At high breast thickness, however, the MGDs received by women with augmented breasts were found to be considerably lower than those relating to their non-augmented counterparts. (author)
Local mammographic density as a predictor of breast cancer
Otsuka, Mayu; Harkness, Elaine F.; Chen, Xin; Moschidis, Emmanouil; Bydder, Megan; Gadde, Soujanya; Lim, Yit Y.; Maxwell, Anthony J.; Evans, Gareth D.; Howell, Anthony; Stavrinos, Paula; Wilson, Mary; Astley, Susan M.
2015-03-01
High overall mammographic density is associated with both an increased risk of developing breast cancer and the risk of cancer being masked. We compared local density at cancer sites in diagnostic images with corresponding previous screening mammograms (priors), and matched controls. VolparaTM density maps were obtained for 54 mammograms showing unilateral breast cancer and their priors which had been previously read as normal. These were each matched to 3 controls on age, menopausal status, hormone replacement therapy usage, body mass index and year of prior. Local percent density was computed in 15mm square regions at lesion sites and similar locations in the corresponding images. Conditional logistic regression was used to predict case-control status. In diagnostic and prior images, local density was increased at the lesion site compared with the opposite breast (medians 21.58%, 9.18%, pcancer than those in the lowest tertile (OR 42.09, 95% CI 5.37-329.94). Those in the highest tertile of VolparaTM gland volume were also more likely to develop cancer (OR 2.89, 95% CI 1.30-6.42). Local density is increased where cancer will develop compared with corresponding regions in the opposite breast and matched controls, and its measurement could enhance computer-aided mammography.
The Discrepancy Principle in Density Estimation
Mildenberger, Thoralf
2011-01-01
We investigate the discrepancy principle, a simple method for choosing smoothing parameters for nonparametric density estimation. The main idea is to maximally smooth subject to a constraint on the data. This technique was originally suggested for the regularization of (deterministic) inverse problems, and in this area, it is one of the most widely known methods for choosing a regularization parameter. However, it has only rarely been applied in statistics, although some authors have suggested its use. The most important examples originate in Statistical Learning Theory and the so-called Data Approximation approach. We unify and extend previous results on kernel density estimation with bandwidths chosen by the discrepancy principle and derive some analogous results for regular histograms. We also show that for certain densities with infinite peaks using the discrepancy principle leads inconsistent estimators. Furthermore, we compare the discrepancy principle to standard methods in a simulation study. The resu...
Multivariate density estimation theory, practice, and visualization
Scott, David W
1992-01-01
Written to convey an intuitive feel for both theory and practice, its main objective is to illustrate what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and quadrivariate information. Major concepts are presented in the context of a histogram in order to simplify the treatment of advanced estimators. Features 12 four-color plates, numerous graphic illustrations as well as a multitude of problems and solutions
Density Estimation in Infinite Dimensional Exponential Families
Sriperumbudur, Bharath; Fukumizu, Kenji; Kumar, Revant; Gretton, Arthur; Hyvärinen, Aapo
2013-01-01
In this paper, we consider an infinite dimensional exponential family, $\\mathcal{P}$ of probability densities, which are parametrized by functions in a reproducing kernel Hilbert space, $H$ and show it to be quite rich in the sense that a broad class of densities on $\\mathbb{R}^d$ can be approximated arbitrarily well in Kullback-Leibler (KL) divergence by elements in $\\mathcal{P}$. The main goal of the paper is to estimate an unknown density, $p_0$ through an element in $\\mathcal{P}$. Standar...
International Nuclear Information System (INIS)
Aim: To investigate the relationship between mammographic breast density (MGD) and background parenchymal enhancement (BPE) at breast MRI and histopathological features of invasive breast cancers. Materials and methods: A total of 178 women with unilateral invasive breast cancer who preoperatively underwent mammography and breast MRI were included in the study. Two radiologists rated MGD and BPE according to BI-RADS criteria in consensus. The relationship between MGD and BPE was investigated, and compared with histopathological features of invasive breast cancers according to the level of MGD and BPE. Results: At MRI, there is no significant difference in the distribution of MGD and BPE of the contralateral breast in women with invasive breast cancer according to menopausal status (p=0.226, 0.384). Women with high MGD (>50% glandular) were more likely to have oestrogen-receptor (ER)-positive breast cancer (p=0.045) and progesterone receptor (PR)-positive breast cancer (p=0.020). With regard to BPE, PR positivity correlated with moderate or marked BPE with borderline significance (p=0.054). Multivariate logistic regression analyses revealed that women with high MGD were less likely to have triple-negative (i.e., a cancer that is ER negative, PR negative, and human epidermal growth factor receptor type 2 [HER2] negative) breast cancer compared with ER (+)/HER2 (−) cancer (OR=0.231, 95% CI: 0.070, 0.760; p=0.016). No association between the histological tumour characteristics and BPE was observed. Conclusion: In women with invasive breast cancer, high MGD is associated with ER positivity of the invasive breast cancer. However, at MRI, BPE of the contralateral breast seems to be independent of tumour characteristics. -- Highlights: •There is no difference in distribution of MGD and BPE of contralateral breast on MRI. •High MGD is associated with ER positivity of the invasive breast cancer. •BPE of the contralateral breast on MRI is independent of tumor
Particle Size Estimation Based on Edge Density
Institute of Scientific and Technical Information of China (English)
WANG Wei-xing
2005-01-01
Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. Such calculations may, for example, be useful fast estimation of particle size in different application areas. The topic is that of estimating average size (=average diameter) of packed particles, from formulas involving edge density, and the edges from moment-based thresholding are used. An average shape factor is involved in the calculations, obtained for some frames from crude partial segmentation. Measurement results from about 80 frames have been analyzed.
Anisotropic Density Estimation in Global Illumination
DEFF Research Database (Denmark)
Schjøth, Lars
2009-01-01
Density estimation employed in multi-pass global illumination algorithms gives cause to a trade-off problem between bias and noise. The problem is seen most evident as blurring of strong illumination features. This thesis addresses the problem, presenting four methods that reduce both noise and...
Uniform Convergence of Multivariate Spectral Density Estimates
Wu, Wei Biao; Zaffaroni, Paolo
2015-01-01
We consider uniform moment convergence of lag-window spectral density estimates for univariate and multivariate stationary processes. Optimal rates of convergence are obtained under mild and easily verifiable conditions. Our theory complements earlier results which primarily concern weak or in-probability convergence.
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High mammographic density might mask breast tumors, resulting in delayed diagnosis or missed cancers. To investigate the association between mammographic density and histopathologic tumor characteristics (histologic type, size, grade, and lymph node status) among women screened in the Norwegian Breast Cancer Screening Program. Information about 1760 screen-detected ductal carcinoma in situ (DCIS) and 7366 invasive breast cancers diagnosed among women aged 50–69 years, 1996–2010, was analyzed. The screening mammograms were classified subjectively according to the amount of fibroglandular tissue into fatty, medium dense, and dense by breast radiologists. Chi-square test was used to compare the distribution of tumor characteristics by mammographic density. Odds ratio (OR) of tumor characteristics by density was estimated by means of logistic regression, adjusting for screening mode (screen-film and full-field digital mammography), and age. Mean and median tumor size of invasive breast cancers was 13.8 and 12 mm, respectively, for women with fatty breasts, and 16.2 and 14 mm for those with dense breasts. Lymph node positive tumors were identified among 20.6% of women with fatty breasts compared with 27.2% of those with dense breasts (P < 0.001). The proportion of DCIS was significantly lower for women with fatty (15.8%) compared with dense breasts (22.0%). Women with dense breasts had an increased risk of large (OR, 1.44; 95% CI, 1.18–1.73) and lymph node positive tumors (OR, 1.26; 95% CI, 1.05–1.51) compared with women with fatty and medium dense breasts. High mammographic density was positively associated with tumor size and lymph node positive tumors
Automatic breast density segmentation: an integration of different approaches
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Mammographic breast density has been found to be a strong risk factor for breast cancer. In most studies, it is assessed with a user-assisted threshold method, which is time consuming and subjective. In this study, we develop a breast density segmentation method that is fully automatic. The method is based on pixel classification in which different approaches known in the literature to segment breast density are integrated and extended. In addition, the method incorporates the knowledge of a trained observer, by using segmentations obtained by the user-assisted threshold method as training data. The method is trained and tested using 1300 digitized film mammographic images acquired with a variety of systems. Results show a high correspondence between the automated method and the user-assisted threshold method. Pearson's correlation coefficient between our method and the user-assisted method is R = 0.911 for percent density and R = 0.895 for dense area, which is substantially higher than the best correlation found in the literature (R = 0.70, R = 0.68). The area under the receiver operating characteristic curve obtained when discriminating between fatty and dense pixels is 0.987. A combination of segmentation strategies outperforms the application of single segmentation techniques.
DENSITY ESTIMATION FOR PROJECTED EXOPLANET QUANTITIES
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Exoplanet searches using radial velocity (RV) and microlensing (ML) produce samples of 'projected' mass and orbital radius, respectively. We present a new method for estimating the probability density distribution (density) of the unprojected quantity from such samples. For a sample of n data values, the method involves solving n simultaneous linear equations to determine the weights of delta functions for the raw, unsmoothed density of the unprojected quantity that cause the associated cumulative distribution function (CDF) of the projected quantity to exactly reproduce the empirical CDF of the sample at the locations of the n data values. We smooth the raw density using nonparametric kernel density estimation with a normal kernel of bandwidth σ. We calibrate the dependence of σ on n by Monte Carlo experiments performed on samples drawn from a theoretical density, in which the integrated square error is minimized. We scale this calibration to the ranges of real RV samples using the Normal Reference Rule. The resolution and amplitude accuracy of the estimated density improve with n. For typical RV and ML samples, we expect the fractional noise at the PDF peak to be approximately 80 n-log2. For illustrations, we apply the new method to 67 RV values given a similar treatment by Jorissen et al. in 2001, and to the 308 RV values listed at exoplanets.org on 2010 October 20. In addition to analyzing observational results, our methods can be used to develop measurement requirements-particularly on the minimum sample size n-for future programs, such as the microlensing survey of Earth-like exoplanets recommended by the Astro 2010 committee.
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Digital breast tomosynthesis (DBT) is a screening and diagnostic modality that acquires images of the breast at multiple angles during a short scan. The Selenia Dimensions (Hologic, Bedford, Mass) DBT system can perform both full-field digital mammography and DBT. The system acquires 15 projections over a 15 deg. angular range (from -7.5 deg. to +7.5 deg.). An important factor in determining the optimal imaging technique for breast tomosynthesis is the radiation dose. In breast imaging, the radiation dose of concern is that deposited in the glandular tissue of the breast because this is the tissue that has a risk of developing cancer. The concept of the normalised mean glandular dose (DgN) has been introduced as the metric for the dose in breast imaging. The DgN is difficult to measure. The Monte Carlo techniques offer an alternative method for a realistic estimation of the radiation dose. The purpose of this work was to use the Monte Carlo code MCNPX technique to generate monoenergetic glandular dose data for estimating the breast tissue dose in tomosynthesis for arbitrary spectra as well as to observe the deposited radiation dose by projection on the glandular portion of the breast in a Selenia Dimensions DBT system. A Monte Carlo simulation of the system was developed to compute the DgN in a craniocaudal view. Monoenergetic X-ray beams from 10 to 49 keV in 1-keV increments were used. The simulation utilised the assumption of a homogeneous breast composition and three compositions (0 % glandular, 50 % glandular and 100 % glandular). The glandular and adipose tissue compositions were specified according ICRU Report 44. A skin layer of 4 mm was assumed to encapsulate the breast on all surfaces. The breast size was varied using the chest wall-to-nipple distance (CND) and compressed breast thickness (t). In this work, the authors assumed a CND of 5 cm and the thicknesses ranged from 2 to 8 cm, in steps of 2 cm. The fractional energy absorption increases (up to 44
Breast Cancer Patients with High Density Mammograms Do Not Have Increased Risk of Death
... density mammograms do not have increased risk of death High mammographic breast density, which is a marker ... does not seem to increase the risk of death among breast cancer patients, according to a study ...
Breast cancer research output, 1945-2008: a bibliometric and density-equalizing analysis
LENUS (Irish Health Repository)
Glynn, Ronan W
2010-12-22
Abstract Introduction Breast cancer is the most common form of cancer among women, with an estimated 194,280 new cases diagnosed in the United States in 2009 alone. The primary aim of this work was to provide an in-depth evaluation of research yield in breast cancer from 1945 to 2008, using large-scale data analysis, the employment of bibliometric indicators of production and quality, and density-equalizing mapping. Methods Data were retrieved from the Web of Science (WOS) Science Citation Expanded database; this was searched using the Boolean operator, \\'OR\\
A detailed breast model and its application for Chinese female breast dose estimation in mammography
International Nuclear Information System (INIS)
The IAEA protocol for breast dosimetry is based on the calculations of Dance which used very simple models of the breast based on the western female data. In order to estimate the dose more precisely in the mammographic examination for the Chinese female, a 3D detailed breast model was constructed. This model contains the detailed structures in the breast, including skin, subcutaneous fat, Cooper's ligaments, and fibro-glandular region containing intra-glandular fat, gland, ductal system, and terminal ductal lobular units. And the size of this breast model was adjusted to represent the characteristic of Chinese female. The glandular tissue conversion coefficients were calculated using this detailed breast model with Monte Carlo code, Geant4. The comparison between the data obtained in this study and the data from Dance was carried out. The discrepancy may come from both the structure and size of the breast models
Sandberg, Maria EC; Li, Jingmei; Hall, Per; Hartman, Mikael; dos-Santos-Silva, Isabel; Humphreys, Keith; Czene, Kamila
2013-01-01
Introduction Mammographic density is a strong risk factor for breast cancer, but it is unknown whether density at first breast cancer diagnosis and changes during follow-up influences risk of non-simultaneous contralateral breast cancer (CBC). Methods We collected mammograms for CBC-patients (cases, N = 211) and unilateral breast cancer patients (controls, N = 211), individually matched on age and calendar period of first breast cancer diagnosis, type of adjuvant therapy and length of follow-...
Height, adiposity and body fat distribution and breast density in young women
Dorgan, Joanne F; Klifa, Catherine; John A. Shepherd; Egleston, Brian L.; Kwiterovich, Peter O.; Himes, John H.; Gabriel, Kelley; Van Horn, Linda; Snetselaar, Linda G; Stevens, Victor J.; Barton, Bruce A; Robson, Alan M.; Lasser, Norman L.; Deshmukh, Snehal; Hylton, Nola M.
2012-01-01
Abstract Introduction Breast density is one of the strongest risk factors for breast cancer, but determinants of breast density in young women remain largely unknown. Methods Associations of height, adiposity and body fat distribution with percentage dense breast volume (%DBV) and absolute dense breast volume (ADBV) were evaluated in a cross-sectional study of 174 healthy women, 25 to 29 years old. Adiposity and body fat distribution were measured by anthropometry and dual-energy...
Estimating the breast surface using UWB microwave monostatic backscatter measurements.
Winters, David W; Shea, Jacob D; Madsen, Ernest L; Frank, Gary R; Van Veen, Barry D; Hagness, Susan C
2008-01-01
This paper presents an algorithm for estimating the location of the breast surface from scattered ultrawideband (UWB) microwave signals recorded across an antenna array. Knowing the location of the breast surface can improve imaging performance if incorporated as a priori information into recently proposed microwave imaging algorithms. These techniques transmit low-power microwaves into the breast using an antenna array, which in turn measures the scattered microwave signals for the purpose of detecting anomalies or changes in the dielectric properties of breast tissue. Our proposed surface identification algorithm consists of three procedures, the first of which estimates M points on the breast surface given M channels of measured microwave backscatter data. The second procedure applies interpolation and extrapolation to these M points to generate N > M points that are approximately uniformly distributed over the breast surface, while the third procedure uses these N points to generate a 3-D estimated breast surface. Numerical as well as experimental tests indicate that the maximum absolute error in the estimated surface generated by the algorithm is on the order of several millimeters. An error analysis conducted for a basic microwave radar imaging algorithm (least-squares narrowband beamforming) indicates that this level of error is acceptable. A key advantage of the algorithm is that it uses the same measured signals that are used for UWB microwave imaging, thereby minimizing patient scan time and avoiding the need for additional hardware. PMID:18232368
Directory of Open Access Journals (Sweden)
Mary Mockus
2015-06-01
Conclusions and general significance: While reproductive characteristics, in particular parity, generally demonstrated independent associations with postmenopausal breast density and E, P and DHEA levels, T levels showed concordant inverse associations with age-at-first birth and breast density. These findings suggest that reproductive effects and later life salivary sex steroid hormone levels may have independent effects on later life breast density and cancer risk.
Conroy, Shannon M; Koga, Karin; Woolcott, Christy G.; Dahl, Timothy; Byrne, Celia; Nagata, Chisato; Ursin, Giske; Yaffe, Martin J.; Vachon, Celine M.; Maskarinec, Gertraud
2012-01-01
Alcohol consumption and mammographic density are established risk factors for breast cancer. This study examined whether the association of mammographic density with breast cancer varies by alcohol intake. Mammographic density was assessed in digitized images for 1,207 cases and 1,663 controls from three populations (Japan, Hawaii, California) using a computer-assisted method. Associations were estimated by logistic regression. When comparing ever to never drinking, mean density was similar a...
Mammographic density and breast cancer risk in White and African American Women
Razzaghi, Hilda; Troester, Melissa A.; Gierach, Gretchen L.; Olshan, Andrew F.; Yankaskas, Bonnie C.; Millikan, Robert C.
2012-01-01
Mammographic density is a strong risk factor for breast cancer, but limited data are available in African American (AA) women. We examined the association between mammographic density and breast cancer risk in AA and white women. Cases (n = 491) and controls (n = 528) were from the Carolina Breast Cancer Study (CBCS) who also had mammograms recorded in the Carolina Mammography Registry (CMR). Mammographic density was reported to CMR using Breast Imaging Reporting and Data System (BI-RADS) cat...
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
International Nuclear Information System (INIS)
Breast density (BD) is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate (X2) and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170), fibroglandular 29% (87), heterogeneously dense 5.7% (17), and dense pattern 8.6% (26). Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117) and older than 50 (68.8%, 126/183). Patterns of high breast density (BD) (dense + heterogeneously dense) were observed in 25.6% (30/117) of women ≤50 years and 7.1% (13/183) of women >50. Asymmetry in BD was observed in 22% (66/300). Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300) of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300) of cases, vascular calcification in 150 cases (78.9%), and fat necrosis in 38 cases (20%). Conclusions. Mexican women have a low percentage of high-density patterns
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
Directory of Open Access Journals (Sweden)
Ana Laura Calderón-Garcidueñas
2012-01-01
Full Text Available Breast density (BD is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate ( and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170, fibroglandular 29% (87, heterogeneously dense 5.7% (17, and dense pattern 8.6% (26. Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117 and older than 50 (68.8%, 126/183. Patterns of high breast density (BD (dense + heterogeneously dense were observed in 25.6% (30/117 of women ≤50 years and 7.1% (13/183 of women >50. Asymmetry in BD was observed in 22% (66/300. Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300 of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300 of cases, vascular calcification in 150 cases (78.9%, and fat necrosis in 38 cases (20%. Conclusions. Mexican women have a low percentage of high-density patterns.
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
International Nuclear Information System (INIS)
Breast density (BD) is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate (χ2) and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170), fibroglandular 29% (87), heterogeneously dense 5.7% (17), and dense pattern 8.6% (26). Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117) and older than 50 (68.8%, 126/183). Patterns of high breast density (BD) (dense + heterogeneously dense) were observed in 25.6% (30/117) of women ≤50 years and 7.1% (13/183) of women >50. Asymmetry in BD was observed in 22% (66/300). Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300) of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300) of cases, vascular calcification in 150 cases (78.9%), and fat necrosis in 38 cases (20%). Conclusions. Mexican women have a low percentage of high-density patterns
Mammographic Breast Density Patterns in Asymptomatic Mexican Women
Calderón-Garcidueñas, Ana Laura; Sanabria-Mondragón, Mónica; Hernández-Beltrán, Lourdes; López-Amador, Noé; Cerda-Flores, Ricardo M.
2012-01-01
Breast density (BD) is a risk factor for breast cancer. Aims. To describe BD patterns in asymptomatic Mexican women and the pathological mammographic findings. Methods and Material. Prospective, descriptive, and comparative study. Women answered a questionnaire and their mammograms were analyzed according to BI-RADS. Univariate (χ2) and conditional logistic regression analyses were performed. Results. In 300 women studied the BD patterns were fat 56.7% (170), fibroglandular 29% (87), heterogeneously dense 5.7% (17), and dense pattern 8.6% (26). Prevalence of fat pattern was significantly different in women under 50 years (37.6%, 44/117) and older than 50 (68.8%, 126/183). Patterns of high breast density (BD) (dense + heterogeneously dense) were observed in 25.6% (30/117) of women ≤50 years and 7.1% (13/183) of women >50. Asymmetry in BD was observed in 22% (66/300). Compression cone ruled out underlying disease in 56 cases. In the remaining 10, biopsy revealed one fibroadenoma, one complex cyst, and 6 invasive and 2 intraductal carcinomas. 2.6% (8/300) of patients had non-palpable carcinomas. Benign lesions were observed in 63.3% (190/300) of cases, vascular calcification in 150 cases (78.9%), and fat necrosis in 38 cases (20%). Conclusions. Mexican women have a low percentage of high-density patterns. PMID:23346398
Multivariate density estimation theory, practice, and visualization
Scott, David W
2015-01-01
David W. Scott, PhD, is Noah Harding Professor in the Department of Statistics at Rice University. The author of over 100 published articles, papers, and book chapters, Dr. Scott is also Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics. He is recipient of the ASA Founder's Award and the Army Wilks Award. His research interests include computational statistics, data visualization, and density estimation. Dr. Scott is also Coeditor of Wiley Interdisciplinary Reviews: Computational Statistics and previous Editor of the Journal of Computational and
Linton, Linda; Martin, Lisa J.; Li, Qing; Huszti, Ella; Minkin, Salomon; John, Esther M.; Rommens, Johanna; Paterson, Andrew D.; Boyd, Norman F
2013-01-01
Introduction Percent mammographic density (PMD) is a strong and highly heritable risk factor for breast cancer. Studies of the role of PMD in familial breast cancer may require controls, such as the sisters of cases, selected from the same 'risk set' as the cases. The use of sister controls would allow control for factors that have been shown to influence risk of breast cancer such as race/ethnicity, socioeconomic status and a family history of breast cancer, but may introduce 'overmatching' ...
Devolli-Disha, Emine; Manxhuka-Kërliu, Suzana; Ymeri, Halit; Kutllovci, Arben
2009-05-01
Breast cancer is the most common cancer and the second most common cause of death from cancer in women.The aim of this studywas to determine which is more accurate imaging test mammography or ultrasound for diagnosis of breast cancer based on the women's age and breast density. We examined 546 patients with breast symptoms, by clinical breast examination, mammography and ultrasound. A total of 546 breast lesions were examined by histopathology analyses. Histopathology results revealed the presence of 259 invasive cancers, and 287 benign lesions. Sensitivity varied significantly with age and breast density. In the 259 women who had both tests, ultrasound had a higher sensitivity than mammography in women younger than 45 years, whereas mammography had a higher sensitivity than ultrasound in women older than 60 years. The sensitivity according to age was 52,1% for mammography and 72,6% for ultrasound. The specificity according to age was 88, 5% for ultrasound and 73, 9% for mammography. Comparing the sensitivity of mammography and ultrasound according to the breast density indicates that mammographic sensitivity was 82,2% among women with predominantly fatty breast, but 23.7% in women with heterogeneous dense breasts, with the increase of fibro glandular density the level of sensitivity with mammography decreases, while ultrasonographic sensitivity was 71,1% among women with predominantly fatty breast and 57,0% for heterogeneous dense breasts. Our data indicate that sensitivity and specificity of ultrasound was statistically significantly greater than mammography in patients with breast symptoms for the detection of breast cancer and benign lesions particularly in dense breast and in young women. PMID:19485945
Colin, Catherine; Prince, Violaine
2009-01-01
High breast density (HBD) tends to be seen as a significant and independent risk factor for breast cancer. This article describes a methodological and quantitative study of the variables selected by the large DMIST study, i.e., age, hormonal status and breast density, in correlation with cancer occurrence frequency. The statistical analysis of cancer rates in every patient subgroup of a study involving more than 42,000 women in screening, shows that HBD, when isolated from other variables, do...
Unified treatment of the asymptotics of asymmetric kernel density estimators
Hoffmann, Till; Jones, Nick S.
2015-01-01
We extend balloon and sample-smoothing estimators, two types of variable-bandwidth kernel density estimators, by a shift parameter and derive their asymptotic properties. Our approach facilitates the unified study of a wide range of density estimators which are subsumed under these two general classes of kernel density estimators. We demonstrate our method by deriving the asymptotic bias, variance, and mean (integrated) squared error of density estimators with gamma, log-normal, Birnbaum-Saun...
Association between body mass index and breast density using digital mammography
Energy Technology Data Exchange (ETDEWEB)
Kim, Mi Young [Dept. of Diagnostic Radiology, Dankook University Hospital, Cheonan (Korea, Republic of); Kim, Hwa Sun [Dept. of Radiological Technology, Ansan University, Ansan (Korea, Republic of)
2014-12-15
It is well known that low body mass index and younger age are associated with high breast density. Mammographic dense breast has been reported both as a cause of false-negative findings on mammography and as an indicator of increased breast cancer risk. The purpose of this study was to evaluate the association between breast density and body mass index. Furthermore, we considered proper screening method of breast cancer in Korean women. The study was performed on 496 women who underwent health checkup in a university hospital. Age and body mass index were negatively associated with breast density respectively. In postmenopausal women, age and body mass index showed statistically significant association with breast density. Therefore, we should consider sensitive additional method for breast cancer screening especially in younger age and underweight women.
Taghipour, S.; Banjevic, D; Miller, A.B.; Montgomery, N; A K S Jardine; Harvey, B. J.
2013-01-01
Background: The aim of screening is to detect a cancer in the preclinical state. However, a false-positive or a false-negative test result is a real possibility. Methods: We describe invasive breast cancer progression in the Canadian National Breast Screening Study and construct progression models with and without covariates. The effect of risk factors on transition intensities and false-negative probability is investigated. We estimate the transition rates, the sojourn time and sensitivity o...
Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina
2014-03-01
Accurate assessment of a woman's risk to develop specific subtypes of breast cancer is critical for appropriate utilization of chemopreventative measures, such as with tamoxifen in preventing estrogen-receptor positive breast cancer. In this context, we investigate quantitative measures of breast density and parenchymal texture, measures of glandular tissue content and tissue structure, as risk factors for estrogen-receptor positive (ER+) breast cancer. Mediolateral oblique (MLO) view digital mammograms of the contralateral breast from 106 women with unilateral invasive breast cancer were retrospectively analyzed. Breast density and parenchymal texture were analyzed via fully-automated software. Logistic regression with feature selection and was performed to predict ER+ versus ER- cancer status. A combined model considering all imaging measures extracted was compared to baseline models consisting of density-alone and texture-alone features. Area under the curve (AUC) of the receiver operating characteristic (ROC) and Delong's test were used to compare the models' discriminatory capacity for receptor status. The density-alone model had a discriminatory capacity of 0.62 AUC (p=0.05). The texture-alone model had a higher discriminatory capacity of 0.70 AUC (p=0.001), which was not significantly different compared to the density-alone model (p=0.37). In contrast the combined density-texture logistic regression model had a discriminatory capacity of 0.82 AUC (prisk for estrogen-receptor positive breast cancer and could be useful in triaging women into appropriate risk-reduction strategies.
Kyoo il Kim
2006-01-01
This paper studies the uniform convergence rate of the turncated SNP (semi-nonparametric) density estimator. Using the uniform convergence rate result we obtain, we propose a test statistic testing the equivalence of two unknown densities where two densities are estimated using the SNP estimator and supports of densities are possibly unbounded.
ESTIMATING MICROORGANISM DENSITIES IN AEROSOLS FROM SPRAY IRRIGATION OF WASTEWATER
This document summarizes current knowledge about estimating the density of microorganisms in the air near wastewater management facilities, with emphasis on spray irrigation sites. One technique for modeling microorganism density in air is provided and an aerosol density estimati...
A nonparametric copula density estimator incorporating information on bivariate marginals
Cheng, Yu-Hsiang; Huang, Tzee-Ming
2016-01-01
We propose a copula density estimator that can include information on bivariate marginals when the information is available. We use B-splines for copula density approximation and include information on bivariate marginals via a penalty term. Our estimator satisfies the constraints for a copula density. Under mild conditions, the proposed estimator is consistent.
Energy Technology Data Exchange (ETDEWEB)
Baek, Ji Eun [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of); Kim, Sung Hun, E-mail: rad-ksh@catholic.ac.kr [Department of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of); Lee, Ah Won [Department of Hospital Pathology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea (Korea, Republic of)
2014-08-15
Objective: To evaluate whether the degree of background parenchymal enhancement affects the accuracy of tumor size estimation based on breast MRI. Methods: Three hundred and twenty-two patients who had known breast cancer and underwent breast MRIs were recruited in our study. The total number of breast cancer cases was 339. All images were assessed retrospectively for the level of background parenchymal enhancement based on the BI-RADS criteria. Maximal lesion diameters were measured on the MRIs, and tumor types (mass vs. non-mass) were assessed. Tumor size differences between the MRI-based estimates and estimates based on pathological examinations were analyzed. The relationship between accuracy and tumor types and clinicopathologic features were also evaluated. Results: The cases included minimal (47.5%), mild (28.9%), moderate (12.4%) and marked background parenchymal enhancement (11.2%). The tumors of patients with minimal or mild background parenchymal enhancement were more accurately estimated than those of patients with moderate or marked enhancement (72.1% vs. 56.8%; p = 0.003). The tumors of women with mass type lesions were significantly more accurately estimated than those of the women with non-mass type lesions (81.6% vs. 28.6%; p < 0.001). The tumor of women negative for HER2 was more accurately estimated than those of women positive for HER2 (72.2% vs. 51.6%; p = 0.047). Conclusion: Moderate and marked background parenchymal enhancement is related to the inaccurate estimation of tumor size based on MRI. Non-mass type breast cancer and HER2-positive breast cancer are other factors that may cause inaccurate assessment of tumor size.
International Nuclear Information System (INIS)
Objective: To evaluate whether the degree of background parenchymal enhancement affects the accuracy of tumor size estimation based on breast MRI. Methods: Three hundred and twenty-two patients who had known breast cancer and underwent breast MRIs were recruited in our study. The total number of breast cancer cases was 339. All images were assessed retrospectively for the level of background parenchymal enhancement based on the BI-RADS criteria. Maximal lesion diameters were measured on the MRIs, and tumor types (mass vs. non-mass) were assessed. Tumor size differences between the MRI-based estimates and estimates based on pathological examinations were analyzed. The relationship between accuracy and tumor types and clinicopathologic features were also evaluated. Results: The cases included minimal (47.5%), mild (28.9%), moderate (12.4%) and marked background parenchymal enhancement (11.2%). The tumors of patients with minimal or mild background parenchymal enhancement were more accurately estimated than those of patients with moderate or marked enhancement (72.1% vs. 56.8%; p = 0.003). The tumors of women with mass type lesions were significantly more accurately estimated than those of the women with non-mass type lesions (81.6% vs. 28.6%; p < 0.001). The tumor of women negative for HER2 was more accurately estimated than those of women positive for HER2 (72.2% vs. 51.6%; p = 0.047). Conclusion: Moderate and marked background parenchymal enhancement is related to the inaccurate estimation of tumor size based on MRI. Non-mass type breast cancer and HER2-positive breast cancer are other factors that may cause inaccurate assessment of tumor size
Llobet Azpitarte, Rafael; Pollán, Marina; Antón Guirao, Joaquín; Miranda-García, Josefa; Casals el Busto, María; Martinez Gomez, Inmaculada; Ruiz Perales, Francisco; Pérez Gómez, Beatriz; Salas-Trejo, Dolores; Perez-Cortes, Juan-Carlos
2014-01-01
The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density(MD) in a more objective and accurate way than via visua...
Directory of Open Access Journals (Sweden)
Jia-Min B Pang
Full Text Available To investigate the cellular and immunophenotypic basis of mammographic density in women at high risk of breast cancer.Mammograms and targeted breast biopsies were accrued from 24 women at high risk of breast cancer. Mammographic density was classified into Wolfe categories and ranked by increasing density. The histological composition and immunophenotypic profile were quantified from digitized haematoxylin and eosin-stained and immunohistochemically-stained (ERα, ERβ, PgR, HER2, Ki-67, and CD31 slides and correlated to mammographic density.Increasing mammographic density was significantly correlated with increased fibrous stroma proportion (rs (22 = 0.5226, p = 0.0088 and significantly inversely associated with adipose tissue proportion (rs (22 = -0.5409, p = 0.0064. Contrary to previous reports, stromal expression of ERα was common (19/20 cases, 95%. There was significantly higher stromal PgR expression in mammographically-dense breasts (p=0.026.The proportion of stroma and fat underlies mammographic density in women at high risk of breast cancer. Increased expression of PgR in the stroma of mammographically dense breasts and frequent and unexpected presence of stromal ERα expression raises the possibility that hormone receptor expression in breast stroma may have a role in mediating the effects of exogenous hormonal therapy on mammographic density.
iDensity: an automatic Gabor filter-based algorithm for breast density assessment
Gamdonkar, Ziba; Tay, Kevin; Ryder, Will; Brennan, Patrick C.; Mello-Thoms, Claudia
2015-03-01
Abstract Although many semi-automated and automated algorithms for breast density assessment have been recently proposed, none of these have been widely accepted. In this study a novel automated algorithm, named iDensity, inspired by the human visual system is proposed for classifying mammograms into four breast density categories corresponding to the Breast Imaging Reporting and Data System (BI-RADS). For each BI-RADS category 80 cases were taken from the normal volumes of the Digital Database for Screening Mammography (DDSM). For each case only the left medio-lateral oblique was utilized. After image calibration using the provided tables of each scanner in the DDSM, the pectoral muscle and background were removed. Images were filtered by a median filter and down sampled. Images were then filtered by a filter bank consisting of Gabor filters in six orientations and 3 scales, as well as a Gaussian filter. Three gray level histogram-based features and three second order statistics features were extracted from each filtered image. Using the extracted features, mammograms were separated initially separated into two groups, low or high density, then in a second stage, the low density group was subdivided into BI-RADS I or II, and the high density group into BI-RADS III or IV. The algorithm achieved a sensitivity of 95% and specificity of 94% in the first stage, sensitivity of 89% and specificity of 95% when classifying BIRADS I and II cases, and a sensitivity of 88% and 91% specificity when classifying BI-RADS III and IV.
Zakariyah, N.; Pathy, N. B.; Taib, N. A. M.; Rahmat, K.; Judy, C. W.; Fadzil, F.; Lau, S.; Ng, K. H.
2016-03-01
It has been shown that breast density and obesity are related to breast cancer risk. The aim of this study is to investigate the relationships of breast volume, breast dense volume and volumetric breast density (VBD) with body mass index (BMI) and body fat mass (BFM) for the three ethnic groups (Chinese, Malay and Indian) in Malaysia. We collected raw digital mammograms from 2450 women acquired on three digital mammography systems. The mammograms were analysed using Volpara software to obtain breast volume, breast dense volume and VBD. Body weight, BMI and BFM of the women were measured using a body composition analyser. Multivariable logistic regression was used to determine the independent predictors of increased overall breast volume, breast dense volume and VBD. Indians have highest breast volume and breast dense volume followed by Malays and Chinese. While Chinese are highest in VBD, followed by Malay and Indian. Multivariable analysis showed that increasing BMI and BFM were independent predictors of increased overall breast volume and dense volume. Moreover, BMI and BFM were independently and inversely related to VBD.
Seiji Hashimoto; Syuji Yoshiki; Ryoko Saeki; Yasuhiro Mimura; Ryosuke Ando; Shutaro Nanba
2016-01-01
Traffic accident frequency has been decreasing in Japan in recent years. Nevertheless, many accidents still occur on residential roads. Area-wide traffic calming measures including Zone 30, which discourages traffic by setting a speed limit of 30 km/h in residential areas, have been implemented. However, no objective implementation method has been established. Development of a model for traffic accident density estimation explained by GIS data can enable the determination of dangerous areas o...
Kernel density estimates used in stochastic precipitation generator
Hnilica, J. (Jan); Puš, V.
2014-01-01
The kernel density estimates were tested to be suitable to describe the probability distribution of daily precipitation sums. For this purpose, a stochastic precipitation generator using the kernel density estimates was constructed and it was compared with the LARS-WG generator. The data from meteorological stations from the Cidlina river basin were used to evaluate the performances of the generators. It was found that the kernel density estimates capture the probability density better th...
Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer
Rauh, C.; Hack, C. C.; Häberle, L.; Hein, A.; Engel, A.; Schrauder, M. G.; Fasching, P. A.; Jud, S. M.; Ekici, A.B.; Loehberg, C. R.; Meier-Meitinger, M.; Ozan, S.; Schulz-Wendtland, R.; Uder, M.; A. Hartmann
2012-01-01
Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study w...
Sprague, Brian L.; Trentham-Dietz, Amy; Terry, Mary Beth; Nichols, Hazel B.; Bersch, Andy J.; Buist, Diana S. M.
2008-01-01
The widespread use of ovulation-inducing drugs to enhance fertility has raised concerns regarding potential effects on breast cancer risk, as ovarian stimulation is associated with increases in estrogen and progesterone levels. We investigated the short-term relation between fertility drug use and mammographic breast density, a strong marker of breast cancer risk, among participants in the Group Health Breast Cancer Screening Program. Data linkage with Group Health’s automated pharmacy record...
Concrete density estimation by rebound hammer method
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Ismail, Mohamad Pauzi bin, E-mail: pauzi@nm.gov.my; Masenwat, Noor Azreen bin; Sani, Suhairy bin; Mohd, Shukri [NDT Group, Nuclear Malaysia, Bangi, Kajang, Selangor (Malaysia); Jefri, Muhamad Hafizie Bin; Abdullah, Mahadzir Bin [Material Technology Program, Faculty of Applied Sciences, UiTM, Shah Alam, Selangor (Malaysia); Isa, Nasharuddin bin; Mahmud, Mohamad Haniza bin [Pusat Penyelidikan Mineral, Jabatan Mineral dan Geosains, Ipoh, Perak (Malaysia)
2016-01-22
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite.
Concrete density estimation by rebound hammer method
International Nuclear Information System (INIS)
Concrete is the most common and cheap material for radiation shielding. Compressive strength is the main parameter checked for determining concrete quality. However, for shielding purposes density is the parameter that needs to be considered. X- and -gamma radiations are effectively absorbed by a material with high atomic number and high density such as concrete. The high strength normally implies to higher density in concrete but this is not always true. This paper explains and discusses the correlation between rebound hammer testing and density for concrete containing hematite aggregates. A comparison is also made with normal concrete i.e. concrete containing crushed granite
Using ultrasound tomography to identify the distributions of density throughout the breast
Sak, Mark; Duric, Neb; Littrup, Peter; Sherman, Mark E.; Gierach, Gretchen L.
2016-04-01
Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient's breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.
Diet across the Lifespan and the Association with Breast Density in Adulthood.
Lindgren, Jessica; Dorgan, Joanne; Savage-Williams, Jennifer; Coffman, Donna; Hartman, Terryl
2013-01-01
Studies have shown inconsistent results regarding the association between dietary factors across the lifespan and breast density and breast cancer in women. Breast density is a strong risk factor for breast cancer, and the mechanism through which it influences cancer risk remains unclear. Breast density has been shown to be modifiable, potentially through dietary modifications. The goal of this paper is to summarize the current studies on diet and diet-related factors across all ages, determine which dietary factors show the strongest association with breast density, the most critical age of exposure, and identify future directions. We identified 28 studies, many of which are cross-sectional, and found that the strongest associations are among vitamin D, calcium, dietary fat, and alcohol in premenopausal women. Longitudinal studies with repeated dietary measures as well as the examination of overall diet over time are needed to confirm these findings. PMID:23431461
Diet across the Lifespan and the Association with Breast Density in Adulthood
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Jessica Lindgren
2013-01-01
Full Text Available Studies have shown inconsistent results regarding the association between dietary factors across the lifespan and breast density and breast cancer in women. Breast density is a strong risk factor for breast cancer, and the mechanism through which it influences cancer risk remains unclear. Breast density has been shown to be modifiable, potentially through dietary modifications. The goal of this paper is to summarize the current studies on diet and diet-related factors across all ages, determine which dietary factors show the strongest association with breast density, the most critical age of exposure, and identify future directions. We identified 28 studies, many of which are cross-sectional, and found that the strongest associations are among vitamin D, calcium, dietary fat, and alcohol in premenopausal women. Longitudinal studies with repeated dietary measures as well as the examination of overall diet over time are needed to confirm these findings.
The estimation of body density in rugby union football players.
Bell, W
1995-01-01
The general regression equation of Durnin and Womersley for estimating body density from skinfold thicknesses in young men, was examined by comparing the estimated density from this equation, with the measured density of a group of 45 rugby union players of similar age. Body density was measured by hydrostatic weighing with simultaneous measurement of residual volume. Additional measurements included stature, body mass and skinfold thicknesses at the biceps, triceps, subscapular and suprailia...
Breast density measurements using ultrasound tomography for patients undergoing tamoxifen treatment
Sak, Mark; Duric, Neb; Littrup, Peter; Li, Cuiping; Bey-Knight, Lisa; Sherman, Mark; Boyd, Norman; Gierach, Gretchen
2013-03-01
Women with high breast density have an increased risk of developing breast cancer. Women treated with the selective estrogen receptor modulator tamoxifen for estrogen receptor positive breast cancer experience a 50% reduction in risk of contralateral breast cancer and overall reduction of similar magnitude has been identified among high-risk women receiving the drug for prevention. Tamoxifen has been shown to reduce mammographic density, and in the IBIS-1 chemoprevention trial, risk reduction and decline in density were significantly associated. Ultrasound tomography (UST) is an imaging modality that can create tomographic sound speed images of the breast. These sound speed images are useful because breast density is proportional to sound speed. The aim of this work is to examine the relationship between USTmeasured breast density and the use of tamoxifen. So far, preliminary results for a small number of patients have been observed and are promising. Correlations between the UST-measured density and mammographic density are strong and positive, while relationships between UST density with some patient specific risk factors behave as expected. Initial results of UST examinations of tamoxifen treated patients show that approximately 45% of the patients have a decrease in density in the contralateral breast after only several months of treatment. The true effect of tamoxifen on UST-measured density cannot yet be fully determined until more data are collected. However, these promising results suggest that UST can be used to reliably assess quantitative changes in breast density over short intervals and therefore suggest that UST may enable rapid assessment of density changes associated with therapeutic and preventative interventions.
Statistical Analysis of Distance Estimators with Density Differences and Density Ratios
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Takafumi Kanamori
2014-02-01
Full Text Available Estimating a discrepancy between two probability distributions from samples is an important task in statistics and machine learning. There are mainly two classes of discrepancy measures: distance measures based on the density difference, such as the Lp-distances, and divergence measures based on the density ratio, such as the Φ-divergences. The intersection of these two classes is the L1-distance measure, and thus, it can be estimated either based on the density difference or the density ratio. In this paper, we first show that the Bregman scores, which are widely employed for the estimation of probability densities in statistical data analysis, allows us to estimate the density difference and the density ratio directly without separately estimating each probability distribution. We then theoretically elucidate the robustness of these estimators and present numerical experiments.
International Nuclear Information System (INIS)
Isoflavones are hypothesized to protect against breast cancer, but it is not clear whether they act as oestrogens or anti-oestrogens in breast tissue. Our aim was to determine the effects of taking a red clover-derived isoflavone supplement daily for 1 year on mammographic breast density. Effects on oestradiol, follicle-stimulating hormone (FSH), luteinizing hormone (LH), lymphocyte tyrosine kinase activity and menopausal symptoms were also assessed. A total of 205 women (age range 49–65 years) with Wolfe P2 or DY mammographic breast patterns were randomly assigned to receive either a red clover-derived isoflavone tablet (26 mg biochanin A, 16 mg formononetin, 1 mg genistein and 0.5 mg daidzein) or placebo. Change in mammographic breast density, serum oestradiol, FSH, LH, menopausal symptoms and lymphocyte tyrosine kinase activity from baseline to 12 months were assessed. A total of 177 women completed the trial. Mammographic breast density decreased in both groups but the difference between the treatment and placebo was not statistically significant. There was a significant interaction between treatment group and oestrogen receptor (ESR1) PvuII polymorphism for the change in estimated percentage breast density (mean ± standard deviation): TT isoflavone 1.4 ± 12.3% and TT placebo -9.6 ± 14.2%; CT isoflavone -5.2 ± 12.0% and CT placebo -2.8 ± 10.3%; and CC isoflavone -3.4 ± 9.7% and CC placebo -1.1 ± 9.5%. There were no statistically significant treatment effects on oestradiol, FSH, or LH (assessed only in postmenopausal women), or on lymphocyte tyrosine kinase activity. Baseline levels of menopausal symptoms were low, and there were no statistically significant treatment effects on frequency of hot flushes or other menopausal symptoms. In contrast to studies showing that conventional hormone replacement therapies increase mammographic breast density, the isoflavone supplement did not increase mammographic breast density in this population of women
Estimation of scattered radiation in digital breast tomosynthesis
Diaz, O.; Dance, D. R.; Young, K. C.; Elangovan, P.; Bakic, P. R.; Wells, K.
2014-08-01
Digital breast tomosynthesis (DBT) is a promising technique to overcome the tissue superposition limitations found in planar 2D x-ray mammography. However, as most DBT systems do not employ an anti-scatter grid, the levels of scattered radiation recorded within the image receptor are significantly higher than that observed in planar 2D x-ray mammography. Knowledge of this field is necessary as part of any correction scheme and for computer modelling and optimisation of this examination. Monte Carlo (MC) simulations are often used for this purpose, however they are computationally expensive and a more rapid method of calculation is desirable. This issue is addressed in this work by the development of a fast kernel-based methodology for scatter field estimation using a detailed realistic DBT geometry. Thickness-dependent scatter kernels, which were validated against the literature with a maximum discrepancy of 4% for an idealised geometry, have been calculated and a new physical parameter (air gap distance) was used to estimate more accurately the distribution of scattered radiation for a series of anthropomorphic breast phantom models. The proposed methodology considers, for the first time, the effects of scattered radiation from the compression paddle and breast support plate, which can represent more than 30% of the total scattered radiation recorded within the image receptor. The results show that the scatter field estimator can calculate scattered radiation images in an average of 80 min for projection angles up to 25° with equal to or less than a 10% error across most of the breast area when compared with direct MC simulations.
Estimation of scattered radiation in digital breast tomosynthesis
International Nuclear Information System (INIS)
Digital breast tomosynthesis (DBT) is a promising technique to overcome the tissue superposition limitations found in planar 2D x-ray mammography. However, as most DBT systems do not employ an anti-scatter grid, the levels of scattered radiation recorded within the image receptor are significantly higher than that observed in planar 2D x-ray mammography. Knowledge of this field is necessary as part of any correction scheme and for computer modelling and optimisation of this examination. Monte Carlo (MC) simulations are often used for this purpose, however they are computationally expensive and a more rapid method of calculation is desirable. This issue is addressed in this work by the development of a fast kernel-based methodology for scatter field estimation using a detailed realistic DBT geometry. Thickness-dependent scatter kernels, which were validated against the literature with a maximum discrepancy of 4% for an idealised geometry, have been calculated and a new physical parameter (air gap distance) was used to estimate more accurately the distribution of scattered radiation for a series of anthropomorphic breast phantom models. The proposed methodology considers, for the first time, the effects of scattered radiation from the compression paddle and breast support plate, which can represent more than 30% of the total scattered radiation recorded within the image receptor. The results show that the scatter field estimator can calculate scattered radiation images in an average of 80 min for projection angles up to 25° with equal to or less than a 10% error across most of the breast area when compared with direct MC simulations. (paper)
Uniform consistency of generalized kernel estimators of quantile density
Cheng, C.
1995-01-01
Various smoothing methods for quantile density estimation are unified into a generalized kernel smoothing. Based on a stochastic upper bound of the derivatives sequence for a sequence of smoothed Brownian bridges, uniform in-probability consistency of generalized kernel quantile density estimators on any closed subinterval of the open unit interval is derived.
Nonparametric volatility density estimation for discrete time models.
A.J. van Es; P.J.C. Spreij; J.H. van Zanten
2005-01-01
Abstract: We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants. A Fourier type deconvolution kernel density estimator based on the logarithm of the squared process i
Density estimation using the trapping web design: A geometric analysis
Link, W.A.; Barker, R.J.
1994-01-01
Population densities for small mammal and arthropod populations can be estimated using capture frequencies for a web of traps. A conceptually simple geometric analysis that avoid the need to estimate a point on a density function is proposed. This analysis incorporates data from the outermost rings of traps, explaining large capture frequencies in these rings rather than truncating them from the analysis.
Quantification of breast density with dual energy mammography: An experimental feasibility study
International Nuclear Information System (INIS)
Purpose: Breast density, the percentage of glandular breast tissue, has been shown to be a strong indicator of breast cancer risk. A quantitative method to measure breast density with dual energy mammography was investigated using physical phantoms. Methods: The dual energy mammography system used a tungsten anode x-ray tube with a 50 μm rhodium beam filter for low energy images and a 300 μm copper beam filter for high energy images. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Four different phantom studies were used to evaluate the technique. The first study consisted of phantoms with thicknesses of 2.5-8.5 cm in 0.5 cm steps with variable densities centered at a mean of 28%. The second study consisted of phantoms at a fixed thickness of 4.0 cm, which ranged in densities from 0% to 100% in increments of 12.5%. The third study consisted of 4.0 cm thick phantoms at densities of 25%, 50% and 75% each imaged at three areal sizes, approximately 62.5, 125, and 250 cm2, in order to assess the effect of breast size on density measurement. The fourth study consisted of step phantoms designed to more closely mimic the shape of a female breast with maximal thicknesses from 3.0 to 7.0 cm at a fixed density of 50%. All images were corrected for x-ray scatter. Results: The RMS errors in breast density measurements were 0.44% for the variable thickness phantoms, 0.64% for the variable density phantoms, 2.87% for the phantoms of different areal sizes, and 4.63% for step phantoms designed to closely resemble the shape of a breast. Conclusions: The results of the phantom studies indicate that dual energy mammography can be used to measure breast density with an RMS error of approximately 5%.
Contribution of breast density to the volume of the augmented breast: A preliminary study
Hill, Sean M; Huettner, Franziska; Murray, John; Elwood, Eric; Barrick, Rebecca; Jones, Glyn
2011-01-01
Breast augmentation is one of the most common procedures performed, and obtaining symmetry and the correct postoperative volume is of the utmost importance. Currently, three-dimensional analysis is used to calculate breast volume, shape, size, etc, which aids the surgeon in deciding on the correct implant size. This study used three-dimensional analysis on 38 breasts (21 women) to measure breast volume and compare it with the implant size, in addition to comparing the results with breast dens...
Current Source Density Estimation for Single Neurons
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Dorottya Cserpán
2014-03-01
Full Text Available Recent developments of multielectrode technology made it possible to measure the extracellular potential generated in the neural tissue with spatial precision on the order of tens of micrometers and on submillisecond time scale. Combining such measurements with imaging of single neurons within the studied tissue opens up new experimental possibilities for estimating distribution of current sources along a dendritic tree. In this work we show that if we are able to relate part of the recording of extracellular potential to a specific cell of known morphology we can estimate the spatiotemporal distribution of transmembrane currents along it. We present here an extension of the kernel CSD method (Potworowski et al., 2012 applicable in such case. We test it on several model neurons of progressively complicated morphologies from ball-and-stick to realistic, up to analysis of simulated neuron activity embedded in a substantial working network (Traub et al, 2005. We discuss the caveats and possibilities of this new approach.
Continuous iterated density estimation evolutionary algorithms within the IDEA framework
Bosman, P.A.N.; Thierens, D.
2001-01-01
In this paper, we formalize the notion of performing optimization by iterated density estimation evolutionary algorithms as the IDEA framework. These algorithms build probabilistic models and estimate probability densities based upon a selection of available points. We show how these probabilistic models can be built and used for different probability density functions within the IDEA framework. We put the emphasis on techniques for vectors of continuous random variables and thereby introduce...
Angiogenesis in Paget's Disease of the Vulva and the Breast: Correlation with Microvessel Density
Crow, Julie C.; Perrett, Christopher W.; Patricia E. Ellis; Wong Te Fong, L. F.; MacLean, Allan B.
2012-01-01
Our understanding of the pathogenesis of Paget's disease of the vulva and the breast remains limited. Current evidence supports the fact that angiogenesis plays an important role in the pathogenesis of several diseases. Therefore, we sought to define its role, as correlated with microvessel density, in Paget's disease of the vulva and the breast. Microvessels were analysed using anti-von Willebrand factor antibody in 105 cases of Paget's disease of the vulva and the breast comprising 71 cases...
Crowd Density Estimation based on Improved Harris Algorithm & Optics Alg.
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Cheng Xu
2014-05-01
Full Text Available In this paper, we propose a method to estimate crowd density using improved Harris and Optics Algorithm. First of all, the images are pre-processed, corner features of the crowd are detected by the improved Harris algorithm, and then the formed density point data will be analyzed. Then, we use the optics density clustering theory to analyze the corner characters of crowd density which based on the distribution of the feature points. At last, the crowd density is estimated by the machine learning algorithm. The experiments are using PETS2009 database and the self-shooting datasets. The proposed approach has been tested on a number of image sequences, and it has good performance.The results show that our approach is superior to other methods, compared to the original Harris algorithm. Our method improves the efficiency of estimation and has a significant impact on preventing the accidents of crowd area with high density.
Sample size re-estimation in a breast cancer trial
Hade, Erinn; Jarjoura, David; Wei, Lai
2016-01-01
Background During the recruitment phase of a randomized breast cancer trial, investigating the time to recurrence, we found evidence that the failure probabilities used at the design stage were too high. Since most of the methodological research involving sample size re-estimation has focused on normal or binary outcomes, we developed a method which preserves blinding to re-estimate sample size in our time to event trial. Purpose A mistakenly high estimate of the failure rate at the design stage may reduce the power unacceptably for a clinically important hazard ratio. We describe an ongoing trial and an application of a sample size re-estimation method that combines current trial data with prior trial data or assumes a parametric model to re-estimate failure probabilities in a blinded fashion. Methods Using our current blinded trial data and additional information from prior studies, we re-estimate the failure probabilities to be used in sample size re-calculation. We employ bootstrap resampling to quantify uncertainty in the re-estimated sample sizes. Results At the time of re-estimation data from 278 patients was available, averaging 1.2 years of follow up. Using either method, we estimated an increase of 0 for the hazard ratio proposed at the design stage. We show that our method of blinded sample size re-estimation preserves the Type I error rate. We show that when the initial guess of the failure probabilities are correct; the median increase in sample size is zero. Limitations Either some prior knowledge of an appropriate survival distribution shape or prior data is needed for re-estimation. Conclusions In trials when the accrual period is lengthy, blinded sample size re-estimation near the end of the planned accrual period should be considered. In our examples, when assumptions about failure probabilities and HRs are correct the methods usually do not increase sample size or otherwise increase it by very little. PMID:20392786
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Kristina M Blackmore
Full Text Available Mammographic density (MD, associated with higher water and lower fat content in the breast, is strongly related to breast cancer risk. Optical attenuation spectroscopy (OS is a non-imaging method of evaluating breast tissue composition by red and near-infrared light transmitted through the breast that, unlike mammography, does not involve radiation. OS provides information on wavelength dependent light scattering of tissue and on absorption by water, lipid, oxy-, deoxy-hemoglobin. We propose that OS could be an alternative marker of breast cancer risk and that OS breast tissue measures will be associated with MD. In the present analysis, we developed an algorithm to estimate breast tissue composition and light scattering parameters using a spectrally constrained global fitting procedure employing a diffuse light transport model. OS measurements were obtained from 202 pre- and post-menopausal women with normal mammograms. Percent density (PD and dense area (DA were measured using Cumulus. The association between OS tissue composition and PD and DA was analyzed using linear regression adjusted for body mass index. Among pre-menopausal women, lipid content was significantly inversely associated with square root transformed PD (β = -0.05, p = 0.0002 and DA (β = -0.05, p = 0.019; water content was significantly positively associated with PD (β = 0.06, p = 0.008. Tissue oxygen saturation was marginally inversely associated with PD (β = -0.03, p = 0.057 but significantly inversely associated with DA (β = -0.10, p = 0.002. Among post-menopausal women lipid and water content were significantly associated (negatively and positively, respectively with PD (β lipid = -0.08, β water = 0.14, both p<0.0001 and DA (β lipid = -0.10, p<0.0001; β water = 0.11, p = 0.001. The association between OS breast content and PD and DA is consistent with more proliferation in dense tissue of younger women, greater lipid content in low density tissue and higher water
Age as a predictive factor of mammographic breast density in Jamaican women
Energy Technology Data Exchange (ETDEWEB)
Soares, Deanne; Reid, Marvin; James, Michael
2002-06-01
AIM: We sought to determine the relationship between age, and other clinical characteristics such as parity, oestrogen use, dietary factors and menstrual history on breast density in Jamaican women. METHODS AND MATERIALS: A retrospective study was done of 891 patients who attended the breast imaging unit. The clinical characteristics were extracted from the patient records. Mammograms were assessed independently by two radiologists who were blinded to the patient clinical characteristics. Breast densities were assigned using the American College of Radiology (ACR) classification. RESULTS: The concordance between the ACR classification of breast density between the two independent radiologists was 92% with k = 0.76 (SE = 0.02, P < 0.001). Women with low breast density were heavier (81.3 {+-} 15.5 kg vs 68.4 {+-} 14.3 kg,P < 0.0001, mean {+-} standard deviation (SD)) and more obese (body mass index (BMI), 30.3 {+-} 5.8 kg m{sup -2} vs 26.0 {+-} 5.2 kg m{sup -2}, P < 0.0001). Mammographic breast density decreased with age. The age adjusted odds ratios (ORs) for predictors significantly related to high breast density were parity, OR = 0.79 (95%CI:0.71, 0.88), weight, OR = 0.92 (95% CI:0.91, 0.95), BMI, OR = 0.83 (95% CI:0.78, 0.89), menopause, OR = 0.51 (95% CI:0.36, 0.74) and a history of previous breast surgery, OR 1.6 (95% CI:1.1, 2.3). CONCLUSION: The rate decline of breast density with age in our population was influenced by parity and body composition. Soares, D. et al. (2002)
On The Density Estimation by Super-Parametric Method
Tsai, Yeong-Shyeong; Hsu, Ying-Lin; Shung, Mung-Chung
2007-01-01
The super-parametric density estimators and its related algorism were suggested by Y. -S. Tsai et al [7]. The number of parameters is unlimited in the super- parametric estimators and it is a general theory in sense of unifying or connecting nonparametric and parametric estimators. Before applying to numerical examples, we can not give any comment of the estimators. In this paper, we will focus on the implementation, the computer programming, of the algorism and strategies of choosing window ...
Estimators of integrals of powers of density derivatives
Rodney C Wolff; Peter Hall
2006-01-01
Simple kernel-type estimators of integrals of general powers of general derivatives of probability densities are proposed. They are based on two simple properties, and in many circumstances enjoy optimal convergence rate.
KERNEL SPATIAL DENSITY ESTIMATION IN INFINITE DIMENSION SPACE
Dabo-Niang, Sophie; Yao, Anne-Françoise
2011-01-01
In this paper, we propose a nonparametric estimation of the spatial density of a functional stationary random field. This later is with values in some infinite dimensional space and admitted a density with respect to some reference measure. The weak and strong consistencies of the estimator are shown and rates of convergence are given. Special attention is paid to the links between the probabilities of small balls in the concerned infinite dimensional space and the rates of convergence. The p...
Evaluating parasite densities and estimation of parameters in transmission systems
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Heinzmann D.
2008-09-01
Full Text Available Mathematical modelling of parasite transmission systems can provide useful information about host parasite interactions and biology and parasite population dynamics. In addition good predictive models may assist in designing control programmes to reduce the burden of human and animal disease. Model building is only the first part of the process. These models then need to be confronted with data to obtain parameter estimates and the accuracy of these estimates has to be evaluated. Estimation of parasite densities is central to this. Parasite density estimates can include the proportion of hosts infected with parasites (prevalence or estimates of the parasite biomass within the host population (abundance or intensity estimates. Parasite density estimation is often complicated by highly aggregated distributions of parasites within the hosts. This causes additional challenges when calculating transmission parameters. Using Echinococcus spp. as a model organism, this manuscript gives a brief overview of the types of descriptors of parasite densities, how to estimate them and on the use of these estimates in a transmission model.
Darker, Iain T.; Chen, Yan; Gale, Alastair G.
2011-03-01
Higher breast density is associated with a greater chance of developing breast cancer. Additionally, it is well known that higher mammographic breast density is associated with increased difficulty in accurately identifying breast cancer. However, comparatively little is known of the reliability of breast density judgements. All UK breast screeners (primarily radiologists and technologists) annually participate in the PERFORMS self-assessment scheme where they make several judgements about series of challenging recent screening cases of known outcomes. As part of this process, for each case, they provide a radiological assessment of the likelihood of cancer on a confidence scale, alongside an assessment of case density using a three point scale. Analysis of the data from two years of the scheme found that the degree of agreement on case density was significantly greater than no agreement (p < .001). However, only a moderate degree of inter-rater reliability was exhibited (κ = .44) with significant differences between the occupational groups. The reasons for differences between the occupational groups and the relationship between agreement on density rating and case reading ability are explored.
Correlation of Asymmetric Breast Density Findings in Mammograms with Cytologic Findings
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"M. Sirus
2005-08-01
Full Text Available Introduction & objectives: Mammography has had a major impact on the early detection of breast cancer; its ability to locate early stage cancer provides the physicians and patients with several treatment op-tions. Many studies have assessed the predictive value of specific mamaographic findings; however, few studies have covered asymmetric breast tissue, which has been reported to occur in 3% of all mammograms. Asymmetric breast tissue is usually benign and ap-pears secondary to variations in normal breast tissue, postoperative changes, or hormone replacement ther-apy. However, it may also indicate a developing mass or an underlying cancer. Patients & Methods: In this study, of the 2360 pa-tients referred to Seyedoshohada hospital for mam-mography during 1997-1998, 112 had asymmetric breast density in their mammographic reports from which 76 were selected. They later underwent FNA after clinical breast examination. Results: The incidence of asymmetric breast density finding in mamographies was reported to be 4.75% in this study. Half of the patients had clinical findings in their breast examination such as palpable breast mass. Normal cytologic findings were observed in 59.2% of the patients; 32.8% had non-proliferative lesions, 2.6% had hyperplasia without atypism, 1.3% had hy-perplasia with atypism, and in 1.3% carcinoma was detected. Discussion: Asymmetric breast tissue densities are frequently encountered at screening and diagnostic mammography. These findings are significant because they may indicate a neoplasm, especially if an associ-ated palpable mass is present. Once these lesions are detected at standard mammography, a thorough knowledge of the patient’s clinical history plus sup-plementary breast imaging with additional mammo-graphic views and ultrasound will allow more accu-rate interpretation of these potentially perplexing soft-tissue findings.
Quantification of Regional Breast Density in Four Quadrants Using 3D MRI—A Pilot Study
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Peter T. Fwu
2015-08-01
Full Text Available PURPOSE: This study presented a three-dimensional magnetic resonance (MR–based method to separate a breast into four quadrants for quantitative measurements of the quadrant breast volume (BV and density. METHODS: Breast MR images from 58 healthy women were studied. The breast and the fibroglandular tissue were segmented by using a computer-based algorithm. A breast was divided into four quadrants using two perpendicular planes intersecting at the nipple or the nipple-centroid line. After the separation, the BV, the fibroglandular tissue volume, and the percent density (PD were calculated. The symmetry of the quadrant BV in the left and right breasts separated by using the nipple alone, or the nipple-centroid line, was compared. RESULTS: The quadrant separation made on the basis of the nipple-centroid line showed closer BVs in four quadrants than using the nipple alone. The correlation and agreement for the BV in corresponding quadrants of the left and the right breasts were improved after the nipple-centroid reorientation. Among the four quadrants, PD was the highest in the lower outer and the lowest in the upper outer (significant than the other three quadrants (P < .05. CONCLUSIONS: We presented a quantitative method to divide a breast into four quadrants. The reorientation based on the nipple-centroid line improved the left to right quadrant symmetry, and this may provide a better standardized method to measure quantitative quadrant density. The cancer occurrence rates are known to vary in different sites of a breast, and our method may provide a tool for investigating its association with the quantitative breast density.
Mean thermospheric density estimation derived from satellite constellations
Li, Alan; Close, Sigrid
2015-10-01
This paper defines a method to estimate the mean neutral density of the thermosphere given many satellites of the same form factor travelling in similar regions of space. A priori information to the estimation scheme include ranging measurements and a general knowledge of the onboard ADACS, although precise measurements are not required for the latter. The estimation procedure seeks to utilize order statistics to estimate the probability of the minimum drag coefficient achievable, and amalgamating all measurements across multiple time periods allows estimation of the probability density of the ballistic factor itself. The model does not depend on prior models of the atmosphere; instead we require estimation of the minimum achievable drag coefficient which is based upon physics models of simple shapes in free molecular flow. From the statistics of the minimum, error statistics on the estimated atmospheric density can be calculated. Barring measurement errors from the ranging procedure itself, it is shown that with a constellation of 10 satellites, we can achieve a standard deviation of roughly 4% on the estimated mean neutral density. As more satellites are added to the constellation, the result converges towards the lower limit of the achievable drag coefficient, and accuracy becomes limited by the quality of the ranging measurements and the probability of the accommodation coefficient. Comparisons are made to existing atmospheric models such as NRLMSISE-00 and JB2006.
Law, Yan Nei; Lieng, Monica Keiko; Li, Jingmei; Khoo, David Aik-Aun
2014-03-01
Breast cancer is the most common cancer and second leading cause of cancer death among women in the US. The relative survival rate is lower among women with a more advanced stage at diagnosis. Early detection through screening is vital. Mammography is the most widely used and only proven screening method for reliably and effectively detecting abnormal breast tissues. In particular, mammographic density is one of the strongest breast cancer risk factors, after age and gender, and can be used to assess the future risk of disease before individuals become symptomatic. A reliable method for automatic density assessment would be beneficial and could assist radiologists in the evaluation of mammograms. To address this problem, we propose a density classification method which uses statistical features from different parts of the breast. Our method is composed of three parts: breast region identification, feature extraction and building ensemble classifiers for density assessment. It explores the potential of the features extracted from second and higher order statistical information for mammographic density classification. We further investigate the registration of bilateral pairs and time-series of mammograms. The experimental results on 322 mammograms demonstrate that (1) a classifier using features from dense regions has higher discriminative power than a classifier using only features from the whole breast region; (2) these high-order features can be effectively combined to boost the classification accuracy; (3) a classifier using these statistical features from dense regions achieves 75% accuracy, which is a significant improvement from 70% accuracy obtained by the existing approaches.
Spatially Adaptive Density Estimation by Localised Haar Projections
Gach, Florian; Spokoiny, Vladimir
2011-01-01
Given a random sample from some unknown density $f_0: \\mathbb R \\to [0, \\infty)$ we devise Haar wavelet estimators for $f_0$ with variable resolution levels constructed from localised test procedures (as in Lepski, Mammen, and Spokoiny (1997, Ann. Statist.)). We show that these estimators adapt to spatially heterogeneous smoothness of $f_0$, simultaneously for every point $x$ in a fixed interval, in sup-norm loss. The thresholding constants involved in the test procedures can be chosen in practice under the idealised assumption that the true density is locally constant in a neighborhood of the point $x$ of estimation, and an information theoretic justification of this practice is given.
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Poellinger, Alexander, E-mail: alexander.poellinger@charite.de [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); El-Ghannam, Sahra; Diekmann, Susanne; Fischer, Thomas [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); Kristiansen, Glen [Universitätsklinikum Bonn, Department of Pathology, Sigmund-Freud-Str. 25, D-53127 Bonn (Germany); Fritzsche, Florian [Institut für Histologie und Zytologie, Bahnhofplatz 11, Postfach, 9101 Herisau (Switzerland); Fallenberg, Eva [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany); Morawietz, Lars [Diagnostik Ernst von Bergmann GmbH, Charlottenstr. 72, 14467 Potsdam (Germany); Diekmann, Felix [Charité, Universitätsmedizin Berlin, Department of Radiology, Augustenburger Platz 1, 13353 Berlin (Germany)
2014-12-15
Highlights: • We correlate capillary density of breast lesions with MRM. • Capillary density correlates with tumor enhancement for all lesions. • However no such correlation exists for the malignant or benign groups separately. • Mean vessel number of lymphatic vessels do not correlate with tumor enhancement.These results might be of help in the workup of MR-guided breast biopsies. • These results might be of help in the workup of MR-guided breast biopsies. - Abstract: Objective: To correlate capillary density of breast lesions using the markers D2-40, CD31, and CD34 with early and late enhancement of magnetic resonance mammography (MRM). Materials and methods: The local ethics committee approved this study, and informed consent was available from all patients. The study included 64 women with 66 histologically proven breast lesions (41 malignant, 25 benign). MR-enhancement 1 min after contrast medium administration was determined in the tumor (I{sub t1}/I{sub t0} ratio) and in comparison to the surrounding tissue (I{sub t1}/I{sub t1-fat} ratio). Capillary density was quantified based on immunohistological staining with D2-40, CD31, and CD34 in breast tumors and surrounding breast tissue. Mean capillary densities were correlated with contrast enhancement in the tumor and surrounding breast tissue. The Kruskal–Wallis test was used to test whether lesions with different MR enhancement patterns differed in terms of capillary density. Results: For CD34, there was statistically significant correlation between capillary density and tumor enhancement (r = 0.329, p = 0.012), however not for the malignant or benign groups separately. Mean vessel number identified by staining with D2-40 and CD31 did not correlate significantly with tumor enhancement (D2-40: r = −0.188, p = 0.130; CD31: r = 0.095, p = 0.448). There were no statistically significant differences in capillary density between breast lesions with delayed enhancement or a plateau and lesions showing
International Nuclear Information System (INIS)
Highlights: • We correlate capillary density of breast lesions with MRM. • Capillary density correlates with tumor enhancement for all lesions. • However no such correlation exists for the malignant or benign groups separately. • Mean vessel number of lymphatic vessels do not correlate with tumor enhancement.These results might be of help in the workup of MR-guided breast biopsies. • These results might be of help in the workup of MR-guided breast biopsies. - Abstract: Objective: To correlate capillary density of breast lesions using the markers D2-40, CD31, and CD34 with early and late enhancement of magnetic resonance mammography (MRM). Materials and methods: The local ethics committee approved this study, and informed consent was available from all patients. The study included 64 women with 66 histologically proven breast lesions (41 malignant, 25 benign). MR-enhancement 1 min after contrast medium administration was determined in the tumor (It1/It0 ratio) and in comparison to the surrounding tissue (It1/It1-fat ratio). Capillary density was quantified based on immunohistological staining with D2-40, CD31, and CD34 in breast tumors and surrounding breast tissue. Mean capillary densities were correlated with contrast enhancement in the tumor and surrounding breast tissue. The Kruskal–Wallis test was used to test whether lesions with different MR enhancement patterns differed in terms of capillary density. Results: For CD34, there was statistically significant correlation between capillary density and tumor enhancement (r = 0.329, p = 0.012), however not for the malignant or benign groups separately. Mean vessel number identified by staining with D2-40 and CD31 did not correlate significantly with tumor enhancement (D2-40: r = −0.188, p = 0.130; CD31: r = 0.095, p = 0.448). There were no statistically significant differences in capillary density between breast lesions with delayed enhancement or a plateau and lesions showing washout (Kruskal
International Nuclear Information System (INIS)
A methodology is presented to estimate cumulative breast dose and breast cancer risk for women exposed to repeated fluoroscopic chest examinations during air collapse therapy for pulmonary tuberculosis. Medical record abstraction, physician interview, patient contact, machine exposure measurements, and absorbed dose computations were combined to estimate average breast doses for 1047 Massachusetts women who were treated between 1930 and 1954. The methodology presented considers breast size and composition, patient orientation, x-ray field size and location, beam quality, type of examination, machine exposure rate, and exposure time during fluoroscopic examinations. The best estimate for the risk of radiation-induced cancer for the women living longer than 10 years after initial fluoroscopic exposure is 6.2 excess breast cancers per million woman-year-rad with 90% confidence limits of 2.8 and 10.7 cancers/106 WY-rad. When breast cancer risk is considered as a function of absorbed dose in the breast, instead of as a function of the number of fluoroscopic examinations, a linear dose--response relationship over the range of estimated doses is consistent with the data. However, because of the uncertainty due to small-sample variability and because of the wide range of assumptions regarding certain fluoroscopy conditions, other dose--response relationships are compatible with the data
Crowd Density and Counting Estimation Based on Image Textural Feature
Directory of Open Access Journals (Sweden)
Jianjie Yang
2014-10-01
Full Text Available This paper proposes an image textural analytical method for estimating the crowd density and counting. At first, the target detection is conducted to obtain the foreground image. This crowd image is used to calculate the gray level co-occurrence matrix (GLCM. Then, according to the characteristic values of the gray level co-occurrence matrix, i.e., energy, entropy, contrast, homogeneity, we use support vector machine (SVM to estimate crowd density. Simultaneously, the method of linear regression is used to estimate the crowd counting. The accuracy of evaluation is improved since we extract the target image textural traits to overcome the influence of background for estimation results. Finally, the experimental results show that the proposed approaches of crowd density and counting are feasible and effective
Angiogenesis in Paget's Disease of the Vulva and the Breast: Correlation with Microvessel Density
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Patricia E. Ellis
2012-01-01
Full Text Available Our understanding of the pathogenesis of Paget's disease of the vulva and the breast remains limited. Current evidence supports the fact that angiogenesis plays an important role in the pathogenesis of several diseases. Therefore, we sought to define its role, as correlated with microvessel density, in Paget's disease of the vulva and the breast. Microvessels were analysed using anti-von Willebrand factor antibody in 105 cases of Paget's disease of the vulva and the breast comprising 71 cases of Paget's disease of the vulva, including 8 cases with invasive disease, and 34 cases of Paget's disease of the breast. The latter included 12 cases with DCIS, 5 cases with both DCIS and invasive carcinoma, and 6 with carcinoma alone. Eleven cases had no underlying tumour identified. Increased microvessel density was demonstrated in Paget's disease of the breast with DCIS and with carcinoma alone compared to Paget's disease of the breast alone, <0.08 and <0.013, respectively. There were no significant differences in microvessel density in the vulval cases. Neovascularisation is an important process in the development of Paget's disease of the breast. Other biological and molecular processes are more involved in the pathogenesis of Paget's disease of the vulva.
Institute of Scientific and Technical Information of China (English)
Lukui Yang; Long Li; Xiangyu Cui; Dalei Yang
2015-01-01
Objective The purpose of this study was to evaluate the distribution of vascular endothelial growth factor (VEGF) and CD105-microvessel density (MVD) in invasive breast carcinomas. We also aimed to analyze the relationship between VEGF and MVD expression with other standard prognostic parameters associated with invasive breast cancer, such as size, grade, stage of the cancer, metastases, and tumor recurrence. Methods Immunohistochemistry via the Ultra SensitiveTM S-P method was used to detect VEGF and MVD expression in 128 cases of invasive breast carcinoma. Specimens were evaluated for CD105 expres-sion. Positively stained microvessels were counted in dense vascular foci under 400× magnification. MVD in the peripheral area adjacent to the lesion and in the central area within the lesion in invasive breast carcinomas and benign leisions groups were also assessed. Fifty cases of benign breast disease tissue were selected as the control group. Results Results showed that 64.1% of invasive breast cancer samples were VEGF-positive, higher than in benign breast disease tissue (22.0%, P 0.05). MVD of the peripheral area adja-cent to the lesion was significantly higher than those central area within the lesion in both invasive breast cancer and benign breast disease groups (P 50 years) or the two tumor diameter groups (≤2 cm vs.>2 cm), P > 0.05. Conclusion Overexpression of VEGF and MVD may be important biological markers for invasion and lymph node and distant metastases of invasive breast cancer. Combined detection of the two tumor mark-ers could provide better prognostic monitoring for disease recurrence and metastasis, as wel as aid with clinical staging of breast tumors. Prediction of the risk for metastasis and recurrence, as wel as recurrence patterns based on VEGF and MVD post-surgery, could aid design of better fol ow-up regimens and appro-priate treatment strategies for breast cancer patients.
Atmospheric Density Corrections Estimated from Fitted Drag Coefficients
McLaughlin, C. A.; Lechtenberg, T. F.; Mance, S. R.; Mehta, P.
2010-12-01
Fitted drag coefficients estimated using GEODYN, the NASA Goddard Space Flight Center Precision Orbit Determination and Geodetic Parameter Estimation Program, are used to create density corrections. The drag coefficients were estimated for Stella, Starlette and GFZ using satellite laser ranging (SLR) measurements; and for GEOSAT Follow-On (GFO) using SLR, Doppler, and altimeter crossover measurements. The data analyzed covers years ranging from 2000 to 2004 for Stella and Starlette, 2000 to 2002 and 2005 for GFO, and 1995 to 1997 for GFZ. The drag coefficient was estimated every eight hours. The drag coefficients over the course of a year show a consistent variation about the theoretical and yearly average values that primarily represents a semi-annual/seasonal error in the atmospheric density models used. The atmospheric density models examined were NRLMSISE-00 and MSIS-86. The annual structure of the major variations was consistent among all the satellites for a given year and consistent among all the years examined. The fitted drag coefficients can be converted into density corrections every eight hours along the orbit of the satellites. In addition, drag coefficients estimated more frequently can provide a higher frequency of density correction.
Density estimation using KNN and a potential model
Lu, Yonggang; Qiao, Jiangang; Liao, Li; Yang, Wuyang
2013-10-01
Density-based clustering methods are usually more adaptive than other classical methods in that they can identify clusters of various shapes and can handle noisy data. A novel density estimation method is proposed using both the knearest neighbor (KNN) graph and a hypothetical potential field of the data points to capture the local and global data distribution information respectively. An initial density score computed using KNN is used as the mass of the data point in computing the potential values. Then the computed potential is used as the new density estimation, from which the final clustering result is derived. All the parameters used in the proposed method are determined from the input data automatically. The new clustering method is evaluated by comparing with K-means++, DBSCAN, and CSPV. The experimental results show that the proposed method can determine the number of clusters automatically while producing competitive clustering results compared to the other three methods.
Kernel density estimation of a multidimensional efficiency profile
Poluektov, Anton
2014-01-01
Kernel density estimation is a convenient way to estimate the probability density of a distribution given the sample of data points. However, it has certain drawbacks: proper description of the density using narrow kernels needs large data samples, whereas if the kernel width is large, boundaries and narrow structures tend to be smeared. Here, an approach to correct for such effects, is proposed that uses an approximate density to describe narrow structures and boundaries. The approach is shown to be well suited for the description of the efficiency shape over a multidimensional phase space in a typical particle physics analysis. An example is given for the five-dimensional phase space of the $\\Lambda_b^0\\to D^0p\\pi$ decay.
Comparison of bone mineral density in young patients with breast cancer and healthy women
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Sousan Kolahi
2014-05-01
Full Text Available BACKGROUND: Almost 1 in 8 women will have breast cancer during their lifetime. Several risk factors were identified; however, 70% of females with breast cancer have no risk factors. Many risk factors are associated with sex steroid hormones. Some studies have been focused on identification of the indices of cumulative exposures to estrogen during the patients’ life. One of these indicators is bone mineral density (BMD. Our aim was the comparison of BMD in young patients with and without breast cancer, and finding a relationship between breast cancer and bone density. METHODS: In this case-control study, 120 people were enrolled; 40 patients with breast cancer and 80 normal healthy persons as control group. Measurement of BMD was performed in both groups and compared. RESULTS: Both groups were matched in age, weight, age at menarche, age at first marriage and first pregnancy, number of pregnancies over 32 weeks and lactation period, and taking supplemental calcium and vitamin D. However, there was a significant difference between the two groups in terms of estrogen intake, family history of breast cancer, and history of breast masses (P = 0.03, P = 0.03, P ≤ 0.01, respectively. A significant difference was found between BMD, bone mineral content (BMC, and t-scores of lumbar spine of the two groups; they were higher in the control group (P = 0.08, P ≤ 0.01, P = 0.06, respectively. CONCLUSIONS: This study shows that bone mineral density of young patients with breast cancer is not higher than normal similar age females; thus, BMD is not directly a risk factor for breast cancer.
Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring
DEFF Research Database (Denmark)
Kallenberg, Michiel Gijsbertus J; Petersen, Peter Kersten; Nielsen, Mads;
2016-01-01
Mammographic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. When the learned features are used as...... the input to a simple classifier, two different tasks can be addressed: i) breast density segmentation, and ii) scoring of mammographic texture. The proposed model learns features at multiple scales. To control the models capacity a novel sparsity regularizer is introduced that incorporates both...... lifetime and population sparsity. We evaluated our method on three different clinical datasets. Our state-of-the-art results show that the learned breast density scores have a very strong positive relationship with manual ones, and that the learned texture scores are predictive of breast cancer. The model...
State of the Art in Photon Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Bouchard, Guillaume;
2012-01-01
scattering. Since its introduction, photon-density estimation has been significantly extended in computer graphics with the introduction of: specialized techniques that intelligently modify the positions or bandwidths to reduce visual error using a small number of photons, approaches that eliminate error...... completely in the limit, and methods that use higher-order samples and queries to reduce error in participating media. This two-part course explains how to implement all these latest advances in photon-density estimation. It begins with a short introduction using classical photon mapping, but the remainder...
State of the Art in Photon-Density Estimation
DEFF Research Database (Denmark)
Hachisuka, Toshiya; Jarosz, Wojciech; Georgiev, Iliyan;
2013-01-01
completely in the limit, and methods that use higher-order samples and queries to reduce error in participating media. This two-part course explains how to implement all these latest advances in photon-density estimation. It begins with a short introduction using classical photon mapping, but the remainder...... of the course provides new, hands-on explanations of the latest developments in this area by experts in each technique. Attendees gain concrete and practical understanding of the latest developments in photon-density-estimation techniques that have not been presented before in SIGGRAPH courses....
Comparison of bone mineral density in young patients with breast cancer and healthy women
Sousan Kolahi; Hamid Noshad; Jamal Eivazi Ziaei; Alireza Nikanfar; Parvin Shakori Partovi; Iraj Asvadi Kermani; Farid Panahi; Nassim Mahmoudzade
2014-01-01
BACKGROUND: Almost 1 in 8 women will have breast cancer during their lifetime. Several risk factors were identified; however, 70% of females with breast cancer have no risk factors. Many risk factors are associated with sex steroid hormones. Some studies have been focused on identification of the indices of cumulative exposures to estrogen during the patients’ life. One of these indicators is bone mineral density (BMD). Our aim was the comparison of BMD in young patients with and without brea...
The estimation of body density in rugby union football players.
Bell, W
1995-03-01
The general regression equation of Durnin and Womersley for estimating body density from skinfold thicknesses in young men, was examined by comparing the estimated density from this equation, with the measured density of a group of 45 rugby union players of similar age. Body density was measured by hydrostatic weighing with simultaneous measurement of residual volume. Additional measurements included stature, body mass and skinfold thicknesses at the biceps, triceps, subscapular and suprailiac sites. The estimated density was significantly different from the measured density (P 0.05), total errors ranging from 0.0067 to 0.0092 g ml-1. An exploratory assessment was also made of the effect of fatness and aerobic fitness on the prediction equations. The equations should be applied to players of similar age and playing ability, and for the purpose of identifying group characteristics. Application of the equations to individuals may give rise to errors of between -3.9% to +2.5% total body fat in two-thirds of cases. PMID:7788218
Forecasting Electricity Smart Meter Data Using Conditional Kernel Density Estimation
Arora, Siddharth; Taylor, James W.
2014-01-01
The recent advent of smart meters has led to large micro-level datasets. For the first time, the electricity consumption at individual sites is available on a near real-time basis. Efficient management of energy resources, electric utilities, and transmission grids, can be greatly facilitated by harnessing the potential of this data. The aim of this study is to generate probability density estimates for consumption recorded by individual smart meters. Such estimates can assist decision making...
Density Estimation in Several Populations With Uncertain Population Membership
Ma, Yanyuan
2011-09-01
We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.
Fu, Wanyi; Tian, Xiaoyu; Sturgeon, Gregory; Agasthya, Greeshma; Segars, William Paul; Goodsitt, Mitchell M.; Kazerooni, Ella A.; Samei, Ehsan
2016-04-01
In thoracic CT, organ-based tube current modulation (OTCM) reduces breast dose by lowering the tube current in the 120° anterior dose reduction zone of patients. However, in practice the breasts usually expand to an angle larger than the dose reduction zone. This work aims to simulate a breast positioning technique (BPT) to constrain the breast tissue to within the dose reduction zone for OTCM and to evaluate the corresponding potential reduction in breast dose. Thirteen female anthropomorphic computational phantoms were studied (age range: 27-65 y.o., weight range: 52-105.8 kg). Each phantom was modeled in the supine position with and without application of the BPT. Attenuation-based tube current (ATCM, reference mA) was generated by a ray-tracing program, taking into account the patient attenuation change in the longitudinal and angular plane (CAREDose4D, Siemens Healthcare). OTCM was generated by reducing the mA to 20% between +/- 60° anterior of the patient and increasing the mA in the remaining projections correspondingly (X-CARE, Siemens Healthcare) to maintain the mean tube current. Breast tissue dose was estimated using a validated Monte Carlo program for a commercial scanner (SOMATOM Definition Flash, Siemens Healthcare). Compared to standard tube current modulation, breast dose was significantly reduced using OTCM by 19.8+/-4.7%. With the BPT, breast dose was reduced by an additional 20.4+/-6.5% to 37.1+/-6.9%, using the same CTDIvol. BPT was more effective for phantoms simulating women with larger breasts with the average breast dose reduction of 30.2%, 39.2%, and 49.2% from OTCMBP to ATCM, using the same CTDIvol for phantoms with 0.5, 1.5, and 2.5 kg breasts, respectively. This study shows that a specially designed BPT improves the effectiveness of OTCM.
A new approach for estimating the density of liquids.
Sakagami, T; Fuchizaki, K; Ohara, K
2016-10-01
We propose a novel approach with which to estimate the density of liquids. The approach is based on the assumption that the systems would be structurally similar when viewed at around the length scale (inverse wavenumber) of the first peak of the structure factor, unless their thermodynamic states differ significantly. The assumption was implemented via a similarity transformation to the radial distribution function to extract the density from the structure factor of a reference state with a known density. The method was first tested using two model liquids, and could predict the densities within an error of several percent unless the state in question differed significantly from the reference state. The method was then applied to related real liquids, and satisfactory results were obtained for predicted densities. The possibility of applying the method to amorphous materials is discussed. PMID:27494268
An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
Directory of Open Access Journals (Sweden)
Juan-Carlos Cano
2013-02-01
Full Text Available In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes.
An infrastructureless approach to estimate vehicular density in urban environments.
Sanguesa, Julio A; Fogue, Manuel; Garrido, Piedad; Martinez, Francisco J; Cano, Juan-Carlos; Calafate, Carlos T; Manzoni, Pietro
2013-01-01
In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes. PMID:23435054
An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments
Sanguesa, Julio A.; Fogue, Manuel; Garrido, Piedad; Martinez, Francisco J.; Cano, Juan-Carlos; Calafate, Carlos T.; Manzoni, Pietro
2013-01-01
In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes. PMID:23435054
International Nuclear Information System (INIS)
A formalism is proposed for the estimation of mean glandular dose for breast tomosynthesis, which is a simple extension of the UK, European and IAEA protocols for dosimetry in conventional projection mammography. The formalism introduces t-factors for the calculation of breast dose from a single projection and T-factors for a complete exposure series. Monte Carlo calculations of t-factors have been made for an imaging geometry with full-field irradiation of the breast for a wide range of x-ray spectra, breast sizes and glandularities. The t-factors show little dependence on breast glandularity and tables are provided as a function of projection angle and breast thickness, which may be used for all x-ray spectra simulated. The T-factors for this geometry depend upon the choice of projection angles and weights per projection, but various example calculations gave values in the range 0.93-1.00. T-factors are also provided for the Sectra tomosynthesis system, which employs a scanned narrow-beam imaging geometry. In this quite different configuration, the factor (denoted TS) shows an important dependence on breast thickness, varying between 0.98 and 0.76 for 20 and 110 mm thick breasts, respectively. Additional data are given to extend the current tabulations of g-, c- and s-factors used for dosimetry of conventional 2D mammography.
Estimating neuronal connectivity from axonal and dendritic density fields
Directory of Open Access Journals (Sweden)
Jaap evan Pelt
2013-11-01
Full Text Available Neurons innervate space by extending axonal and dendritic arborizations. When axons and dendrites come in close proximity of each other, synapses between neurons can be formed. Neurons vary greatly in their morphologies and synaptic connections with other neurons. The size and shape of the arborizations determine the way neurons innervate space. A neuron may therefore be characterized by the spatial distribution of its axonal and dendritic 'mass'. A population mean 'mass' density field of a particular neuron type can be obtained by averaging over the individual variations in neuron geometries. Connectivity in terms of candidate synaptic contacts between neurons can be determined directly on the basis of their arborizations but also indirectly on the basis of their density fields. To decide when a candidate synapse can be formed, we previously developed a criterion defining that axonal and dendritic line pieces should cross in 3D and have an orthogonal distance less than a threshold value. In this paper, we developed new methodology for applying this criterion to density fields. We show that estimates of the number of contacts between neuron pairs calculated from their density fields are fully consistent with the number of contacts calculated from the actual arborizations. However, the estimation of the connection probability and the expected number of contacts per connection cannot be calculated directly from density fields, because density fields do not carry anymore the correlative structure in the spatial distribution of synaptic contacts. Alternatively, these two connectivity measures can be estimated from the expected number of contacts by using empirical mapping functions. The neurons used for the validation studies were generated by our neuron simulator NETMORPH. An example is given of the estimation of average connectivity and Euclidean pre- and postsynaptic distance distributions in a network of neurons represented by their population
International Nuclear Information System (INIS)
To compare the conspicuity of different histopathological types of breast cancer according to breast density and mammographic imaging in patients with screen-detected breast cancers undergoing both full-field digital mammography (FFDM) and screen-film mammography (SFM) in the United Kingdom National Health Service Breast Screening Programme (NHSBSP). 185 patients underwent routine screening with SFM followed by further imaging using FFDM with consequent diagnosis of breast cancer. All SFM and soft-copy FFDM images were evaluated by two readers in an independent, retrospective review. The visualisation and conspicuity of the mammographic abnormality were recorded and graded using a four-level scale. Conspicuity of breast cancer was qualitatively evaluated. Breast density and conspicuity were correlated with histopathological diagnosis and inter-observer correlation was calculated. Mixed Model ANOVA demonstrated significant differences between FFDM and SFM (p < 0.001) and breast densities (p = 0.009): conspicuity of the mammographic abnormality (p < 0.001) and visualisation of the dominant mammographic feature (p < 0.001) were significantly greater with FFDM than SFM. This held true for both readers and for all histopathological tumour types with no significant differences between each tumour type. FFDM is significantly superior to SFM for conspicuity of screen-detected breast cancers for all histopathological types and breast densities. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Pinker, Katja [Medical University Vienna, Department of Radiology, Divison of Molecular and Gender Imaging, Vienna (Austria); Medical University Vienna, Department of Radiology, MR Centre of Excellence, Vienna (Austria); Perry, Nicholas [St Bartholomew' s Hospital, Breast Unit, Barts and The London Cancer Centre, London (United Kingdom); The Princess Grace Hospital, The London Breast Institute, London (United Kingdom); Vinnicombe, S.; Shiel, S. [St Bartholomew' s Hospital, Breast Unit, Barts and The London Cancer Centre, London (United Kingdom); Weber, M. [Medical University Vienna, Department of Radiology, Vienna (Austria)
2011-01-15
To compare the conspicuity of different histopathological types of breast cancer according to breast density and mammographic imaging in patients with screen-detected breast cancers undergoing both full-field digital mammography (FFDM) and screen-film mammography (SFM) in the United Kingdom National Health Service Breast Screening Programme (NHSBSP). 185 patients underwent routine screening with SFM followed by further imaging using FFDM with consequent diagnosis of breast cancer. All SFM and soft-copy FFDM images were evaluated by two readers in an independent, retrospective review. The visualisation and conspicuity of the mammographic abnormality were recorded and graded using a four-level scale. Conspicuity of breast cancer was qualitatively evaluated. Breast density and conspicuity were correlated with histopathological diagnosis and inter-observer correlation was calculated. Mixed Model ANOVA demonstrated significant differences between FFDM and SFM (p < 0.001) and breast densities (p = 0.009): conspicuity of the mammographic abnormality (p < 0.001) and visualisation of the dominant mammographic feature (p < 0.001) were significantly greater with FFDM than SFM. This held true for both readers and for all histopathological tumour types with no significant differences between each tumour type. FFDM is significantly superior to SFM for conspicuity of screen-detected breast cancers for all histopathological types and breast densities. (orig.)
Face Value: Towards Robust Estimates of Snow Leopard Densities.
Directory of Open Access Journals (Sweden)
Justine S Alexander
Full Text Available When densities of large carnivores fall below certain thresholds, dramatic ecological effects can follow, leading to oversimplified ecosystems. Understanding the population status of such species remains a major challenge as they occur in low densities and their ranges are wide. This paper describes the use of non-invasive data collection techniques combined with recent spatial capture-recapture methods to estimate the density of snow leopards Panthera uncia. It also investigates the influence of environmental and human activity indicators on their spatial distribution. A total of 60 camera traps were systematically set up during a three-month period over a 480 km2 study area in Qilianshan National Nature Reserve, Gansu Province, China. We recorded 76 separate snow leopard captures over 2,906 trap-days, representing an average capture success of 2.62 captures/100 trap-days. We identified a total number of 20 unique individuals from photographs and estimated snow leopard density at 3.31 (SE = 1.01 individuals per 100 km2. Results of our simulation exercise indicate that our estimates from the Spatial Capture Recapture models were not optimal to respect to bias and precision (RMSEs for density parameters less or equal to 0.87. Our results underline the critical challenge in achieving sufficient sample sizes of snow leopard captures and recaptures. Possible performance improvements are discussed, principally by optimising effective camera capture and photographic data quality.
Kernel density estimates used in stochastic precipitation generator
Czech Academy of Sciences Publication Activity Database
Hnilica, Jan; Puš, V.
Praha: Ústav pro hydrodynamiku, 2014 - (Brych, K.; Tesař, M.), s. 120-124 ISBN 978-80-02-02525-2. [Hydrologie malého povodí 2014. Praha (CZ), 22.04.2014-24.04.2014] Institutional support: RVO:67985874 Keywords : kernel density estimate * daily precipitation sum * stochastic generator Subject RIV: DA - Hydrology ; Limnology
Estimation of a multivariate stochastic volatility density by kernel deconvolution
B. van Es; P. Spreij
2011-01-01
We consider a continuous time stochastic volatility model. The model contains a stationary volatility process. We aim to estimate the multivariate density of the finite-dimensional distributions of this process. We assume that we observe the process at discrete equidistant instants of time. The dist
Corruption clubs: empirical evidence from kernel density estimates
Herzfeld, T.; Weiss, Ch.
2007-01-01
A common finding of many analytical models is the existence of multiple equilibria of corruption. Countries characterized by the same economic, social and cultural background do not necessarily experience the same levels of corruption. In this article, we use Kernel Density Estimation techniques to
Density estimation in tiger populations: combining information for strong inference
Gopalaswamy, Arjun M.; Royle, J. Andrew; Delampady, Mohan; Nichols, James D.; Karanth, K. Ullas; Macdonald, David W.
2012-01-01
A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture–recapture data. The model, which combined information, provided the most precise estimate of density (8.5 ± 1.95 tigers/100 km2 [posterior mean ± SD]) relative to a model that utilized only one data source (photographic, 12.02 ± 3.02 tigers/100 km2 and fecal DNA, 6.65 ± 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.
Density estimates for phase transitions with a trace
Sire, Yannick
2010-01-01
We consider a functional obtained by adding a trace term to the Allen-Cahn phase segregation model and we prove some density estimates for the level sets of the interfaces. We treat in a unified way also the cases of possible degeneracy and singularity of the ellipticity of the model and the quasiminimal case.
Density Estimation Classifiers Uses Geometry of Neighbors Space
Czech Academy of Sciences Publication Activity Database
Jiřina, Marcel
IEEE, 2003 - (Rudas, I.; Szakál, A.) ISBN 963-7154-183. [ICCC 2003. IEEE International Conference on Computational Cybernetics . Siófok (HU), 29.08.2003-31.08.2003] R&D Projects: GA MŠk LN00B096 Keywords : density * estimation * neighbors space * classification Subject RIV: BA - General Mathematics
Nonparametric density estimators based on nonstationary absolutely regular random sequences
Directory of Open Access Journals (Sweden)
Michel Harel
1996-01-01
Full Text Available In this paper, the central limit theorems for the density estimator and for the integrated square error are proved for the case when the underlying sequence of random variables is nonstationary. Applications to Markov processes and ARMA processes are provided.
Regularized Regression and Density Estimation based on Optimal Transport
Burger, M.
2012-03-11
The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).
Ionospheric electron density profile estimation using commercial AM broadcast signals
Yu, De; Ma, Hong; Cheng, Li; Li, Yang; Zhang, Yufeng; Chen, Wenjun
2015-08-01
A new method for estimating the bottom electron density profile by using commercial AM broadcast signals as non-cooperative signals is presented in this paper. Without requiring any dedicated transmitters, the required input data are the measured elevation angles of signals transmitted from the known locations of broadcast stations. The input data are inverted for the QPS model parameters depicting the electron density profile of the signal's reflection area by using a probabilistic inversion technique. This method has been validated on synthesized data and used with the real data provided by an HF direction-finding system situated near the city of Wuhan. The estimated parameters obtained by the proposed method have been compared with vertical ionosonde data and have been used to locate the Shijiazhuang broadcast station. The simulation and experimental results indicate that the proposed ionospheric sounding method is feasible for obtaining useful electron density profiles.
Density estimates for deep-sea gastropod assemblages
Rex, Michael A.; Etter, Ron J.; Nimeskern, Phillip W.
1990-04-01
Extensive boxcore sampling in the Atlantic Continental Slope and Rise study permitted the first precise measurement of gastropod density in the bathyal region of the deep sea. Gastropod density decreases significantly and exponentially with depth (250-3494 m), and density-depth regression lines do not differ significantly in either slope or elevatiob over horizontal scales of approximately 1000 km. The subclasses Prosobranchia and Opisthobranchia both show significant decreases in density with depth. Predatory taxa (neogastropods and opisthobranchs) exhibit significantly steeper declines in density with depth than do taxa dominated by deposit feeders (archaeogastropods and mesogastropods). Members of upper trophic levels may be more sensitive to the reduction in nutrient input with increased depth because of the energy loss between trophic levels in the food chain. A comparison of density estimates of gastropods from boxcore, grab and anchor-dredge samples taken in the same region revealed no significant differences in density-depth relationships among the sampling methods. A synthesis of data from 777 boxcore samples collected from the Atlantic, Caribbean and Pacific over a depth range of 250-7298 m indicates that the decline in gastropod density with depth is a global trend with only moderate inter-regional variation.
Evaluating lidar point densities for effective estimation of aboveground biomass
Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.
2016-01-01
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.
Estimation of Enceladus Plume Density Using Cassini Flight Data
Wang, Eric K.; Lee, Allan Y.
2011-01-01
The Cassini spacecraft was launched on October 15, 1997 by a Titan 4B launch vehicle. After an interplanetary cruise of almost seven years, it arrived at Saturn on June 30, 2004. In 2005, Cassini completed three flybys of Enceladus, a small, icy satellite of Saturn. Observations made during these flybys confirmed the existence of water vapor plumes in the south polar region of Enceladus. Five additional low-altitude flybys of Enceladus were successfully executed in 2008-9 to better characterize these watery plumes. During some of these Enceladus flybys, the spacecraft attitude was controlled by a set of three reaction wheels. When the disturbance torque imparted on the spacecraft was predicted to exceed the control authority of the reaction wheels, thrusters were used to control the spacecraft attitude. Using telemetry data of reaction wheel rates or thruster on-times collected from four low-altitude Enceladus flybys (in 2008-10), one can reconstruct the time histories of the Enceladus plume jet density. The 1 sigma uncertainty of the estimated density is 5.9-6.7% (depending on the density estimation methodology employed). These plume density estimates could be used to confirm measurements made by other onboard science instruments and to support the modeling of Enceladus plume jets.
Zheng, Yuanjie; Wang, Yan; Keller, Brad M.; Conant, Emily; Gee, James C.; Kontos, Despina
2013-02-01
Estimating a woman's risk of breast cancer is becoming increasingly important in clinical practice. Mammographic density, estimated as the percent of dense (PD) tissue area within the breast, has been shown to be a strong risk factor. Studies also support a relationship between mammographic texture and breast cancer risk. We have developed a fullyautomated software pipeline for computerized analysis of digital mammography parenchymal patterns by quantitatively measuring both breast density and texture properties. Our pipeline combines advanced computer algorithms of pattern recognition, computer vision, and machine learning and offers a standardized tool for breast cancer risk assessment studies. Different from many existing methods performing parenchymal texture analysis within specific breast subregions, our pipeline extracts texture descriptors for points on a spatial regular lattice and from a surrounding window of each lattice point, to characterize the local mammographic appearance throughout the whole breast. To demonstrate the utility of our pipeline, and optimize its parameters, we perform a case-control study by retrospectively analyzing a total of 472 digital mammography studies. Specifically, we investigate the window size, which is a lattice related parameter, and compare the performance of texture features to that of breast PD in classifying case-control status. Our results suggest that different window sizes may be optimal for raw (12.7mm2) versus vendor post-processed images (6.3mm2). We also show that the combination of PD and texture features outperforms PD alone. The improvement is significant (p=0.03) when raw images and window size of 12.7mm2 are used, having an ROC AUC of 0.66. The combination of PD and our texture features computed from post-processed images with a window size of 6.3 mm2 achieves an ROC AUC of 0.75.
Open-cluster density profiles derived using a kernel estimator
Seleznev, Anton F
2016-01-01
Surface and spatial radial density profiles in open clusters are derived using a kernel estimator method. Formulae are obtained for the contribution of every star into the spatial density profile. The evaluation of spatial density profiles is tested against open-cluster models from N-body experiments with N = 500. Surface density profiles are derived for seven open clusters (NGC 1502, 1960, 2287, 2516, 2682, 6819 and 6939) using Two-Micron All-Sky Survey data and for different limiting magnitudes. The selection of an optimal kernel half-width is discussed. It is shown that open-cluster radius estimates hardly depend on the kernel half-width. Hints of stellar mass segregation and structural features indicating cluster non-stationarity in the regular force field are found. A comparison with other investigations shows that the data on open-cluster sizes are often underestimated. The existence of an extended corona around the open cluster NGC 6939 was confirmed. A combined function composed of the King density pr...
Can modeling improve estimation of desert tortoise population densities?
Nussear, K.E.; Tracy, C.R.
2007-01-01
The federally listed desert tortoise (Gopherus agassizii) is currently monitored using distance sampling to estimate population densities. Distance sampling, as with many other techniques for estimating population density, assumes that it is possible to quantify the proportion of animals available to be counted in any census. Because desert tortoises spend much of their life in burrows, and the proportion of tortoises in burrows at any time can be extremely variable, this assumption is difficult to meet. This proportion of animals available to be counted is used as a correction factor (g0) in distance sampling and has been estimated from daily censuses of small populations of tortoises (6-12 individuals). These censuses are costly and produce imprecise estimates of g0 due to small sample sizes. We used data on tortoise activity from a large (N = 150) experimental population to model activity as a function of the biophysical attributes of the environment, but these models did not improve the precision of estimates from the focal populations. Thus, to evaluate how much of the variance in tortoise activity is apparently not predictable, we assessed whether activity on any particular day can predict activity on subsequent days with essentially identical environmental conditions. Tortoise activity was only weakly correlated on consecutive days, indicating that behavior was not repeatable or consistent among days with similar physical environments. ?? 2007 by the Ecological Society of America.
Bayesian error estimation in density-functional theory
DEFF Research Database (Denmark)
Mortensen, Jens Jørgen; Kaasbjerg, Kristen; Frederiksen, Søren Lund;
2005-01-01
We present a practical scheme for performing error estimates for density-functional theory calculations. The approach, which is based on ideas from Bayesian statistics, involves creating an ensemble of exchange-correlation functionals by comparing with an experimental database of binding energies...... for molecules and solids. Fluctuations within the ensemble can then be used to estimate errors relative to experiment on calculated quantities such as binding energies, bond lengths, and vibrational frequencies. It is demonstrated that the error bars on energy differences may vary by orders of...
Photo-z Estimation: An Example of Nonparametric Conditional Density Estimation under Selection Bias
Izbicki, Rafael; Freeman, Peter E
2016-01-01
Redshift is a key quantity for inferring cosmological model parameters. In photometric redshift estimation, cosmologists use the coarse data collected from the vast majority of galaxies to predict the redshift of individual galaxies. To properly quantify the uncertainty in the predictions, however, one needs to go beyond standard regression and instead estimate the full conditional density f(z|x) of a galaxy's redshift z given its photometric covariates x. The problem is further complicated by selection bias: usually only the rarest and brightest galaxies have known redshifts, and these galaxies have characteristics and measured covariates that do not necessarily match those of more numerous and dimmer galaxies of unknown redshift. Unfortunately, there is not much research on how to best estimate complex multivariate densities in such settings. Here we describe a general framework for properly constructing and assessing nonparametric conditional density estimators under selection bias, and for combining two o...
International Nuclear Information System (INIS)
Preventive oncology is in need of a risk assessment technique that can identify individuals at high risk for breast cancer and has the ability to monitor the efficacy of a risk reducing intervention. Optical transillumination spectroscopy (OTS) gives information about breast tissue composition and tissue density. OTS is noninvasive and in contrast to mammography, uses nonionizing radiation. It is safe and can be used frequently on younger women, potentially permitting early risk detection and thus increasing the time available for risk reduction interventions to assert their influence. Before OTS can be used as a risk assessment and/or monitoring technique, its predictive ability needs to be demonstrated and maximized through the construction of various mathematical models relating OTS and breast tissue density, and hence, risk. To establish a correlation between OTS and mammographic density principal components analysis (PCA), using risk classification, is calculated. The PCA scores are presented in three-dimensional cluster plots and a plane of differentiation that separates the high and low tissue densities is used to calculate the predictive value. Stratification of PCA for measurement position on the breast in cranial-caudal projection is introduced. Analysis of PCA scores as a function of the volunteer's age and body mass index (BMI) is examined. A small but significant correlation between the component scores and age or BMI is noted but the correlation is dependent on the tissue density category examined. Correction of the component scores for age and BMI is not recommended, since a priori knowledge of a woman's breast tissue density is required. Stratification for the center and distal measurement positions provide a predictive value for OTS above 96%
Probability Density Estimation by Decomposition of Correlation Integral
Czech Academy of Sciences Publication Activity Database
Jiřina, Marcel; Jiřina jr., M.
- : ISRST, 2008 - (Prasad, B.; Sinha, P.; Ram, A.; Kerre, E.), s. 113-119 ISBN 978-1-60651-000-1. [AIPR 2008. International Conference on Artificial Intelligence and Pattern Recognition. Orlando (US), 07.07.2008-10.07.2008] Institutional research plan: CEZ:AV0Z10300504 Keywords : correlation integral * decomposition of correlation integral * probability density estimation * polynomial approximation * classifier Subject RIV: BA - General Mathematics
Probability Density Estimation by Decomposition of Correlation Integral
Czech Academy of Sciences Publication Activity Database
Jiřina, Marcel; Jiřina jr., M.
-: ISRST, 2008 - (Prasad, B.; Sinha, P.; Ram, A.; Kerre, E.), s. 113-119 ISBN 978-1-60651-000-1. [AIPR 2008. International Conference on Artificial Intelligence and Pattern Recognition. Orlando (US), 07.07.2008-10.07.2008] Institutional research plan: CEZ:AV0Z10300504 Keywords : correlation integral * decomposition of correlation integral * probability density estimation * polynomial approximation * classifier Subject RIV: BA - General Mathematics
Density Estimation of Comet 103P/Hartley 2
Bowling, T.; Richardson, J.; Melosh, J.; Thomas, P.
2011-10-01
Our analysis was constrained to the region of the neck that was directly imaged and well illuminated during the encounter. A homogeneous density and a rotation period of 18.34 hours are assumed. Only rotation about the principal axis was accounted for. The principal rotation period was likely shorter on timescales effective for surface modification [2]. Additionally, spin components about minor axes introduce a further degree of error. A global minimum is found for a bulk density ? = 220 kg m-3 (one sigma = 130-620 kg m-3) which corresponds to a comet mass of m = 1.84 x 1011 kg (one sigma = 1.51-5.18 x 1011 kg). This is lower than, but within error ranges of, previous comet density estimates (sec. 4.2 of [3]).
Estimating black bear density using DNA data from hair snares
Gardner, B.; Royle, J. Andrew; Wegan, M.T.; Rainbolt, R.E.; Curtis, P.D.
2010-01-01
DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capturerecapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km2. A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level. ?? The Wildlife Society.
Uncertainties in estimating heart doses from 2D-tangential breast cancer radiotherapy
DEFF Research Database (Denmark)
Lorenzen, Ebbe L; Brink, Carsten; Taylor, Carolyn W; Darby, Sarah C; Ewertz, Marianne
2016-01-01
-based planning scans for 40 patients with left-sided and 10 with right-sided breast cancer. Setup errors and organ motion were simulated using estimated uncertainties. For left-sided patients, mean heart dose was related to maximum heart distance in the medial field. RESULTS: For left-sided breast cancer, mean...... uncertainty of estimates based on individual CT-scans. For right-sided breast cancer patients, mean heart dose based on individual CT-scans was always <1Gy and maximum dose always <5Gy for all three regimens. CONCLUSIONS: The use of stored individual simulator films provides a method for estimating heart......BACKGROUND AND PURPOSE: We evaluated the accuracy of three methods of estimating radiation dose to the heart from two-dimensional tangential radiotherapy for breast cancer, as used in Denmark during 1982-2002. MATERIAL AND METHODS: Three tangential radiotherapy regimens were reconstructed using CT...
Sun, Wei; Jiang, Yi-Zhou; Liu, Yi-Rong; Ma, Ding; Shao, Zhi-Ming
2016-04-12
Luminal breast cancer constitutes a group of highly heterogeneous diseases with a sustained high risk of late recurrence. We aimed to develop comprehensive and practical nomograms to better estimate the long-term survival of luminal breast cancer.Patients with luminal breast cancer diagnosed between 1990 and 2006 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into the training (n = 87,867) and validation (n = 88,215) cohorts. The cumulative incidence function (CIF) and a competing-risks model were used to estimate the probability of breast cancer-specific survival (BCSS) and death from other causes. We integrated significant prognostic factors to build nomograms and subjected the nomograms to bootstrap internal validation and to external validation.We screened 176,082 luminal breast cancer cases. The 5- and 10-year probabilities of overall death were 0.089 and 0.202, respectively. The 5- and 10-year probabilities of breast cancer-specific mortality (BCSM) were 0.053 and 0.112, respectively. Nine independent prognostic factors for both OS and BCSS were integrated to construct the nomograms. The calibration curves for the probabilities of 5- and 10-year OS and BCSS showed excellent agreement between the nomogram prediction and actual observation. The C-indexes of the nomograms were high in both internal validation (0.732 for OS and 0.800 for BCSS) and external validation (0.731 for OS and 0.794 for BCSS).We established nomograms that accurately predict OS and BCSS for patients with luminal breast cancer. The nomograms can identify patients with higher risk of late overall mortality and BCSM, helping physicians in facilitating individualized treatment. PMID:26967253
The Mammographic Density of a Mass Is a Significant Predictor of Breast Cancer
Woods, Ryan W.; Sisney, Gale S.; Salkowski, Lonie R.; Shinki, Kazuhiko; Lin, Yunzhi
2011-01-01
Purpose: To determine whether the mammographic density of noncalcified solid breast masses is associated with malignancy and to measure the agreement between prospective and retrospective assessment. Materials and Methods: The institutional review board approved this study and waived informed consent. Three hundred forty-eight consecutive breast masses in 328 women who underwent image-guided or surgical biopsy between October 2005 and December 2007 were included. All 348 biopsy-proved masses were randomized and assigned to a radiologist who was blinded to biopsy results for retrospective assessment by using the Breast Imaging Reporting and Data System (retrospectively assessed data set). Clinical radiologists prospectively assessed the density of 180 of these masses (prospectively assessed data set). Pathologic result at biopsy was the reference standard. Benign masses were followed for at least 1 year by linking each patient to a cancer registry. Univariate analyses were performed on the retrospectively assessed data set. The association of mass density and malignancy was examined by creating a logistic model for the prospectively assessed data set. Agreement between prospective and retrospective assessments was calculated by using the κ statistic. Results: In the retrospectively assessed data set, 70.2% of high-density masses were malignant, and 22.3% of the isodense or low-density masses were malignant (P < .0001). In the prospective logistic model, high density (odds ratio, 6.6), irregular shape (odds ratio, 9.9), spiculated margin (odds ratio, 20.3), and age (β = 0.09, P < .0001) were significantly associated with the probability of malignancy. The κ value for prospective-retrospective agreement of mass density was 0.53. Conclusion: High mass density is significantly associated with malignancy in both retrospectively and prospectively assessed data sets, with moderate prospective-retrospective agreement. Radiologists should consider mass density as a
A Concept of Approximated Densities for Efficient Nonlinear Estimation
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Virginie F. Ruiz
2002-10-01
Full Text Available This paper presents the theoretical development of a nonlinear adaptive filter based on a concept of filtering by approximated densities (FAD. The most common procedures for nonlinear estimation apply the extended Kalman filter. As opposed to conventional techniques, the proposed recursive algorithm does not require any linearisation. The prediction uses a maximum entropy principle subject to constraints. Thus, the densities created are of an exponential type and depend on a finite number of parameters. The filtering yields recursive equations involving these parameters. The update applies the Bayes theorem. Through simulation on a generic exponential model, the proposed nonlinear filter is implemented and the results prove to be superior to that of the extended Kalman filter and a class of nonlinear filters based on partitioning algorithms.
Image Representation Using EPANECHNIKOV Density Feature Points Estimator
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Tranos Zuva
2013-03-01
Full Text Available In image retrieval most of the existing visual content based representation methods are usually applicationdependent or non robust, making them not suitable for generic applications. These representation methodsuse visual contents such as colour, texture, shape,size etc. Human image recognition is largely basedonshape, thus making it very appealing for image representation algorithms in computer vision.In this paper we propose a generic image representation algorithm using Epanechnikov Density FeaturePoints Estimator (EDFPE. It is invariant to rotation, scale and translation. The image density featurepoints within defined rectangular rings around thegravitational centre of the image are obtained in theform of a vector. The EDFPE is applied to the vector representation of the image. The Cosine AngleDistance (CAD algorithm is used to measure similarity of the images in the database. Quantitativeevaluation of the performance of the system and comparison with other algorithms was done
Image Representation Using EPANECHNIKOV Density Feature Points Estimator
Directory of Open Access Journals (Sweden)
Tranos Zuva
2013-02-01
Full Text Available In image retrieval most of the existing visual content based representation methods are usually application dependent or non robust, making them not suitable for generic applications. These representation methods use visual contents such as colour, texture, shape, size etc. Human image recognition is largely based on shape, thus making it very appealing for image repr esentation algorithms in computer vision. In this paper we propose a generic image representation algorithm using Epanechnikov Density Feature Points Estimator (EDFPE. It is invariant to rotation, scale and translation. The image density feature points within defined rectangular rings around the gravitational centre of the image are obtained in the form of a vector. The EDFPE is applied to the vecto r representation of the image. The Cosine Angle Distance (CAD algorithm is used to measure similarity of the images in the database. Quantitative evaluation of the performance of the system and comparison with other algorithms was done.
Some asymptotic results on density estimators by wavelet projections
Varron, Davit
2012-01-01
Let $(X_i)_{i\\geq 1}$ be an i.i.d. sample on $\\RRR^d$ having density $f$. Given a real function $\\phi$ on $\\RRR^d$ with finite variation and given an integer valued sequence $(j_n)$, let $\\fn$ denote the estimator of $f$ by wavelet projection based on $\\phi$ and with multiresolution level equal to $j_n$. We provide exact rates of almost sure convergence to 0 of the quantity $\\sup_{x\\in H}\\mid \\fn(x)-\\EEE(\\fn)(x)\\mid$, when $n2^{-dj_n}/\\log n \\rar \\infty$ and $H$ is a given hypercube of $\\RRR^...
Atkinson, Charlotte; Warren, Ruth M. L.; Sala, Evis; Dowsett, Mitch; Dunning, Alison M; Healey, Catherine S.; Runswick, Shirley; Day, Nicholas E; Bingham, Sheila
2004-01-01
Abstract Introduction Isoflavones are hypothesized to protect against breast cancer, but it is not clear whether they act as oestrogens or anti-oestrogens in breast tissue. Our aim was to determine the effects of taking a red clover-derived isoflavone supplement daily for 1 year on mammographic breast density. Effects on oestradiol, follicle-stimulating hormone (FSH), luteinizing hormone (LH), lymphocyte tyrosine kinase activity and menopausal symptoms were also assessed. Methods A total of 2...
International Nuclear Information System (INIS)
To compare the pre-and postenhanced power Doppler sonographic (PDS) findings in malignant and benign breast masses and to correlate power Doppler area (PDA) and histologic microvessel density (MVD). Forty-seven women with breast masses (27 malignant and 20 benign) underwent PDS before and after an injection of microbubble contrast agent (Levovist) for five minutes. Using computer-assisted quantification, intratumoral % PDA was calculated. Microvessel density was counted on the digitized image of slides stained with anti CD31 moonclonal antibody. The statistical analysis was performed using t-test to determine the difference of % PDA between malignant and benign masses and between 0.05). MVD was well correlated with % PDA on post-enhancement PDS (r=0.69), and a stronger correlation was seen in malignant masses (r=0.71). Contrast-enhanced PDS is superior in demonstrating the difference of vascularity between malignant and benign breast masses. % PDA after contrast-enhancement exhibited a statistically significant correlation and benign breast masses. %PDA after contrast-enhancement exhibited a statistically significant correlation with histologic MVD.
Estimation of the Space Density of Low Surface Brightness Galaxies
Briggs, F H
1997-01-01
The space density of low surface brightness and tiny gas-rich dwarf galaxies are estimated for two recent catalogs: The Arecibo Survey of Northern Dwarf and Low Surface Brightness Galaxies (Schneider, Thuan, Magri & Wadiak 1990) and The Catalog of Low Surface Brightness Galaxy, List II (Schombert, Bothun, Schneider & McGaugh 1992). The goals are (1) to evaluate the additions to the completeness of the Fisher and Tully (1981) 10 Mpc Sample and (2) to estimate whether the density of galaxies contained in the new catalogs adds a significant amount of neutral gas mass to the the inventory of HI already identified in the nearby, present-epoch universe. Although tiny dwarf galaxies (M_HI < ~10^7 solar masses) may be the most abundant type of extragalactic stellar system in the nearby Universe, if the new catalogs are representative, the LSB and dwarf populations they contain make only a small addition (<10%) to the total HI content of the local Universe and probably constitute even smaller fractions o...
Acoustic Signal based Traffic Density State Estimation using SVM
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Prashant Borkar
2013-06-01
Full Text Available Based on the information present in cumulative acoustic signal acquired from a roadside-installed single microphone, this paper considers the problem of vehicular traffic density state estimation. The occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc are determined by the prevalent traffic density conditions on the road segment. In this work, we extract the short-term spectral envelope features of the cumulative acoustic signals using MFCC (Mel-Frequency Cepstral Coefficients. Support Vector Machines (SVM is used as classifier is used to model the traffic density state as Low (40 Km/h and above, Medium (20-40 Km/h, and Heavy (0-20 Km/h. For the developing geographies where the traffic is non-lane driven and chaotic, other techniques (magnetic loop detectors are inapplicable. SVM classifier with different kernels are used to classify the acoustic signal segments spanning duration of 20–40 s, which results in average classification accuracy of 96.67% for Quadratic kernel function and 98.33% for polynomial kernel function, when entire frames are considered for classification.
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Energy Technology Data Exchange (ETDEWEB)
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
Change-in-ratio density estimator for feral pigs is less biased than closed mark-recapture estimates
Hanson, L.B.; Grand, J.B.; Mitchell, M.S.; Jolley, D.B.; Sparklin, B.D.; Ditchkoff, S.S.
2008-01-01
Closed-population capture-mark-recapture (CMR) methods can produce biased density estimates for species with low or heterogeneous detection probabilities. In an attempt to address such biases, we developed a density-estimation method based on the change in ratio (CIR) of survival between two populations where survival, calculated using an open-population CMR model, is known to differ. We used our method to estimate density for a feral pig (Sus scrofa) population on Fort Benning, Georgia, USA. To assess its validity, we compared it to an estimate of the minimum density of pigs known to be alive and two estimates based on closed-population CMR models. Comparison of the density estimates revealed that the CIR estimator produced a density estimate with low precision that was reasonable with respect to minimum known density. By contrast, density point estimates using the closed-population CMR models were less than the minimum known density, consistent with biases created by low and heterogeneous capture probabilities for species like feral pigs that may occur in low density or are difficult to capture. Our CIR density estimator may be useful for tracking broad-scale, long-term changes in species, such as large cats, for which closed CMR models are unlikely to work. ?? CSIRO 2008.
Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment
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Zheng, Bin, E-mail: zhengb@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Sumkin, Jules H., E-mail: jsumkin@mail.magee.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Zuley, Margarita L., E-mail: zuleyml@upmc.edu [Department of Radiology, Magee Womens Hospital, 300 Halket Street, Pittsburgh, PA 15213 (United States); Wang, Xingwei, E-mail: wangx6@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Klym, Amy H., E-mail: klymah@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States); Gur, David, E-mail: gurd@upmc.edu [Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Pittsburgh, PA 15213 (United States)
2012-11-15
To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 {+-} 0.030, 0.535 {+-} 0.036, 0.567 {+-} 0.031, and 0.719 {+-} 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 {+-} 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.
Bilateral mammographic density asymmetry and breast cancer risk: A preliminary assessment
International Nuclear Information System (INIS)
To improve efficacy of breast cancer screening and prevention programs, it requires a risk assessment model with high discriminatory power. This study aimed to assess classification performance of using computed bilateral mammographic density asymmetry to predict risk of individual women developing breast cancer in near-term. The database includes 451 cases with multiple screening mammography examinations. The first (baseline) examinations of all case were interpreted negative. In the next sequential examinations, 187 cases developed cancer or surgically excised high-risk lesions, 155 remained negative (not-recalled), and 109 were recalled benign cases. From each of two bilateral cranio-caudal view images acquired from the baseline examination, we computed two features of average pixel value and local pixel value fluctuation. We then computed mean and difference of each feature computed from two images. When applying the computed features and other two risk factors (woman's age and subjectively rated mammographic density) to predict risk of cancer development, areas under receiver operating characteristic curves (AUC) were computed to evaluate the discriminatory/classification performance. The AUCs are 0.633 ± 0.030, 0.535 ± 0.036, 0.567 ± 0.031, and 0.719 ± 0.027 when using woman's age, subjectively rated, computed mean and asymmetry of mammographic density, to classify between two groups of cancer-verified and negative cases, respectively. When using an equal-weighted fusion method to combine woman's age and computed density asymmetry, AUC increased to 0.761 ± 0.025 (p < 0.05). The study demonstrated that bilateral mammographic density asymmetry could be a significantly stronger risk factor associated to the risk of women developing breast cancer in near-term than woman's age and assessed mean mammographic density.
Directory of Open Access Journals (Sweden)
Saadatmand Sepideh
2012-10-01
Full Text Available Abstract Background To reduce mortality, women with a family history of breast cancer often start mammography screening at a younger age than the general population. Breast density is high in over 50% of women younger than 50 years. With high breast density, breast cancer incidence increases, but sensitivity of mammography decreases. Therefore, mammography might not be the optimal method for breast cancer screening in young women. Adding MRI increases sensitivity, but also the risk of false-positive results. The limitation of all previous MRI screening studies is that they do not contain a comparison group; all participants received both MRI and mammography. Therefore, we cannot empirically assess in which stage tumours would have been detected by either test. The aim of the Familial MRI Screening Study (FaMRIsc is to compare the efficacy of MRI screening to mammography for women with a familial risk. Furthermore, we will assess the influence of breast density. Methods/Design This Dutch multicentre, randomized controlled trial, with balanced randomisation (1:1 has a parallel grouped design. Women with a cumulative lifetime risk for breast cancer due to their family history of ≥20%, aged 30–55 years are eligible. Identified BRCA1/2 mutation carriers or women with 50% risk of carrying a mutation are excluded. Group 1 receives yearly mammography and clinical breast examination (n = 1000, and group 2 yearly MRI and clinical breast examination, and mammography biennially (n = 1000. Primary endpoints are the number and stage of the detected breast cancers in each arm. Secondary endpoints are the number of false-positive results in both screening arms. Furthermore, sensitivity and positive predictive value of both screening strategies will be assessed. Cost-effectiveness of both strategies will be assessed. Analyses will also be performed with mammographic density as stratification factor. Discussion Personalized breast cancer screening
Estimating tropical-forest density profiles from multibaseline interferometric SAR
Treuhaft, Robert; Chapman, Bruce; dos Santos, Joao Roberto; Dutra, Luciano; Goncalves, Fabio; da Costa Freitas, Corina; Mura, Jose Claudio; de Alencastro Graca, Paulo Mauricio
2006-01-01
Vertical profiles of forest density are potentially robust indicators of forest biomass, fire susceptibility and ecosystem function. Tropical forests, which are among the most dense and complicated targets for remote sensing, contain about 45% of the world's biomass. Remote sensing of tropical forest structure is therefore an important component to global biomass and carbon monitoring. This paper shows preliminary results of a multibasline interfereomtric SAR (InSAR) experiment over primary, secondary, and selectively logged forests at La Selva Biological Station in Costa Rica. The profile shown results from inverse Fourier transforming 8 of the 18 baselines acquired. A profile is shown compared to lidar and field measurements. Results are highly preliminary and for qualitative assessment only. Parameter estimation will eventually replace Fourier inversion as the means to producing profiles.
Some asymptotic results on density estimators by wavelet projections
Varron, Davit
2012-01-01
Let $(X_i)_{i\\geq 1}$ be an i.i.d. sample on $\\RRR^d$ having density $f$. Given a real function $\\phi$ on $\\RRR^d$ with finite variation and given an integer valued sequence $(j_n)$, let $\\fn$ denote the estimator of $f$ by wavelet projection based on $\\phi$ and with multiresolution level equal to $j_n$. We provide exact rates of almost sure convergence to 0 of the quantity $\\sup_{x\\in H}\\mid \\fn(x)-\\EEE(\\fn)(x)\\mid$, when $n2^{-dj_n}/\\log n \\rar \\infty$ and $H$ is a given hypercube of $\\RRR^d$. We then show that, if $n2^{-dj_n}/\\log n \\rar c$ for a constant $c>0$, then the quantity $\\sup_{x\\in H}\\mid \\fn(x)-f\\mid$ almost surely fails to converge to 0.
Estimating Foreign-Object-Debris Density from Photogrammetry Data
Long, Jason; Metzger, Philip; Lane, John
2013-01-01
Within the first few seconds after launch of STS-124, debris traveling vertically near the vehicle was captured on two 16-mm film cameras surrounding the launch pad. One particular piece of debris caught the attention of engineers investigating the release of the flame trench fire bricks. The question to be answered was if the debris was a fire brick, and if it represented the first bricks that were ejected from the flame trench wall, or was the object one of the pieces of debris normally ejected from the vehicle during launch. If it was typical launch debris, such as SRB throat plug foam, why was it traveling vertically and parallel to the vehicle during launch, instead of following its normal trajectory, flying horizontally toward the north perimeter fence? By utilizing the Runge-Kutta integration method for velocity and the Verlet integration method for position, a method that suppresses trajectory computational instabilities due to noisy position data was obtained. This combination of integration methods provides a means to extract the best estimate of drag force and drag coefficient under the non-ideal conditions of limited position data. This integration strategy leads immediately to the best possible estimate of object density, within the constraints of unknown particle shape. These types of calculations do not exist in readily available off-the-shelf simulation software, especially where photogrammetry data is needed as an input.
Blyschak, Kristina; Simick, Michelle K.; Jong, Roberta A.; Lilge, Lothar D.
2003-12-01
Preventive oncology is in need of a risk assessment technique that can identify individuals at high risk for breast cancer and that has the ability to monitor the efficacy of a risk reducing intervention. Optical transillumination spectroscopy (OTS) was shown to give information about breast tissue composition and tissue density. OTS is non-invasive, and in contrast to mammography, uses non-ionizing radiation. It is safe and can be used frequently on younger women, potentially permitting early risk detection and thus increasing the time available for risk reduction interventions to assert their influence. Before OTS can be used as a risk assessment and/or monitoring technique, its predictive ability needs to be demonstrated and maximized through the construction of mathematical models relating OTS and risk. To establish a correlation between OTS and mammographic density, Principle Components Analysis (PCA), using risk classification, is employed. PCA scores are presented in 3D cluster plots and a plane of differentiation that separates high and low tissue density is used to calculate the predictive value. Stratificaiton of PCA for measurement position on the breast in cranial-caudal projection is introduced. Analysis of PCA scores as a function of the volunteer's age and body mass index (BMI) is examined. A small but significant correlation between the component scores and age or BMI is noted but the correlation is dependnet on the tissue density category examined. Correction of the component scores for age and BMI is not recommended, since a priori knowledge of a women's tissue density is required. Stratification for the center and distal measurement positions provides a predictive value for OTS above 96%.
Estimates of transition densities and their derivatives for jump L\\'evy processes
Kaleta, Kamil; Sztonyk, Paweł
2013-01-01
We give upper and lower estimates of densities of convolution semigroups of probability measures under explicit assumptions on the corresponding Levy measure and the Levy--Khinchin exponent. We obtain also estimates of derivatives of densities.
Breast cancer size estimation with MRI in BRCA mutation carriers and other high risk patients
Energy Technology Data Exchange (ETDEWEB)
Mann, R.M., E-mail: r.mann@rad.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Radiology, Nijmegen (Netherlands); Bult, P., E-mail: p.bult@path.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Pathology, Nijmegen (Netherlands); Laarhoven, H.W.M. van, E-mail: h.vanlaarhoven@amc.uva.nl [Academic Medical Centre, University of Amsterdam, Department of Medical Oncology, Amsterdam (Netherlands); Radboud University Nijmegen Medical Centre, Department of Medical Oncology, Nijmegen (Netherlands); Span, P.N., E-mail: p.span@rther.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Radiation Oncology, Nijmegen (Netherlands); Schlooz, M., E-mail: m.schlooz@chir.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Surgery, Nijmegen (Netherlands); Veltman, J., E-mail: j.veltman@zgt.nl [Hospital group Twente (ZGT), Department of Radiology, Almelo (Netherlands); Hoogerbrugge, N., E-mail: n.hoogerbrugge@gen.umcn.nl [Radboud University Nijmegen Medical Centre, Department of Human Genetics, Nijmegen (Netherlands)
2013-09-15
Objective: To assess the value of breast MRI in size assessment of breast cancers in high risk patients, including those with a BRCA 1 or 2 mutation. Guidelines recommend invariably breast MRI screening for these patients and therapy is thus based on these findings. However, the accuracy of breast MRI for staging purposes is only tested in sporadic cancers. Methods: We assessed concordance of radiologic staging using MRI with histopathology in 49 tumors in 46 high risk patients (23 BRCA1, 12 BRCA2 and 11 Non-BRCA patients). The size of the total tumor area (TTA) was compared to pathology. In invasive carcinomas (n = 45) the size of the largest focus (LF) was also addressed. Results: Correlation of MRI measurements with pathology was 0.862 for TTA and 0.793 for LF. TTA was underestimated in 8(16%), overestimated in 5(10%), and correctly measured in 36(73%) cases. LF was underestimated in 4(9%), overestimated in 5(11%), and correctly measured in 36(80%) cases. Impact of BRCA 1 or 2 mutations on the quality of size estimation was not observed. Conclusions: Tumor size estimation using breast MRI in high risk patients is comparable to its performance in sporadic cancers. Therefore, breast MRI can safely be used for treatment planning.
Breast cancer size estimation with MRI in BRCA mutation carriers and other high risk patients
International Nuclear Information System (INIS)
Objective: To assess the value of breast MRI in size assessment of breast cancers in high risk patients, including those with a BRCA 1 or 2 mutation. Guidelines recommend invariably breast MRI screening for these patients and therapy is thus based on these findings. However, the accuracy of breast MRI for staging purposes is only tested in sporadic cancers. Methods: We assessed concordance of radiologic staging using MRI with histopathology in 49 tumors in 46 high risk patients (23 BRCA1, 12 BRCA2 and 11 Non-BRCA patients). The size of the total tumor area (TTA) was compared to pathology. In invasive carcinomas (n = 45) the size of the largest focus (LF) was also addressed. Results: Correlation of MRI measurements with pathology was 0.862 for TTA and 0.793 for LF. TTA was underestimated in 8(16%), overestimated in 5(10%), and correctly measured in 36(73%) cases. LF was underestimated in 4(9%), overestimated in 5(11%), and correctly measured in 36(80%) cases. Impact of BRCA 1 or 2 mutations on the quality of size estimation was not observed. Conclusions: Tumor size estimation using breast MRI in high risk patients is comparable to its performance in sporadic cancers. Therefore, breast MRI can safely be used for treatment planning
International Nuclear Information System (INIS)
This paper introduces a probability density estimator based on Green's function identities. A density model is constructed under the sole assumption that the probability density is differentiable. The method is implemented as a binary likelihood estimator for classification purposes, so issues such as mis-modeling and overtraining are also discussed. The identity behind the density estimator can be interpreted as a real-valued, non-scalar kernel method which is able to reconstruct differentiable density functions.
González, Francisco Javier
2011-01-01
In this work the metabolic heat generated by breast tumors was estimated indirectly and noninvasively from digital infrared images and numerically simulating a simplified breast model and a cancerous tumor, this parameter can be of clinical importance since it has been related to the doubling volume's time and malignancy for that particular tumor. The results indicate that digital infrared imaging has the potential to estimate in a non-invasive way the malignancy of a tumor by calculating its metabolic heat generation from bioheat thermal transfer models.
Medical image segmentation to estimate HER2 gene status in breast cancer
Palacios-Navarro, Guillermo; Acirón-Pomar, José Manuel; Vilchez-Sorribas, Enrique; Zambrano, Eddie Galarza
2016-02-01
This work deals with the estimation of HER2 Gene status in breast tumour images treated with in situ hybridization techniques (ISH). We propose a simple algorithm to obtain the amplification factor of HER2 gene. The obtained results are very close to those obtained by specialists in a manual way. The developed algorithm is based on colour image segmentation and has been included in a software application tool for breast tumour analysis. The developed tool focus on the estimation of the seriousness of tumours, facilitating the work of pathologists and contributing to a better diagnosis.
EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area
DEFF Research Database (Denmark)
Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi
EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of a...
LIMIT THEOREMS FOR KERNEL DENSITY ESTIMATORS IN SPACES OF ARBITRARY NATURE
Directory of Open Access Journals (Sweden)
Orlov A. I.
2015-04-01
Full Text Available Some estimators of the probability density function in spaces of arbitrary nature are used for various tasks in statistics of non-numerical data. Systematic exposition of the theory of such estimators had a start in our work [2]. This article is a direct continuation of the article [2]. We will regularly use references to conditions and theorems of the article [2], in which we introduced several types of nonparametric estimators of the probability density. We studied more linear estimators. In this article we consider particular cases - kernel density estimates in spaces of arbitrary nature. When estimating the density of the one-dimensional random variable, kernel estimators become the Parzen-Rosenblatt estimators. Asymptotic behavior of kernel density estimators in the general case of an arbitrary nature spaces are devoted to Theorem 1 - 8. Under different conditions we prove the consistency and asymptotic normality of kernel density estimators. We have studied uniform convergence. We have introduced the concept of "preferred rate differences" and studied nuclear density estimators based on it. We have also introduced and studied natural affinity measures which are used in the analysis of the asymptotic behavior of kernel density estimators. We have found the asymptotic behavior of dispersions of kernel density estimators and considered the examples including kernel density estimators in finite-dimensional spaces and in the space of square-integrable functions
Theoretical and Experimental Estimations of Volumetric Inductive Phase Shift in Breast Cancer Tissue
González, C. A.; Lozano, L. M.; Uscanga, M. C.; Silva, J. G.; Polo, S. M.
2013-04-01
Impedance measurements based on magnetic induction for breast cancer detection has been proposed in some studies. This study evaluates theoretical and experimentally the use of a non-invasive technique based on magnetic induction for detection of patho-physiological conditions in breast cancer tissue associated to its volumetric electrical conductivity changes through inductive phase shift measurements. An induction coils-breast 3D pixel model was designed and tested. The model involves two circular coils coaxially centered and a human breast volume centrally placed with respect to the coils. A time-harmonic numerical simulation study addressed the effects of frequency-dependent electrical properties of tumoral tissue on the volumetric inductive phase shift of the breast model measured with the circular coils as inductor and sensor elements. Experimentally; five female volunteer patients with infiltrating ductal carcinoma previously diagnosed by the radiology and oncology departments of the Specialty Clinic for Women of the Mexican Army were measured by an experimental inductive spectrometer and the use of an ergonomic inductor-sensor coil designed to estimate the volumetric inductive phase shift in human breast tissue. Theoretical and experimental inductive phase shift estimations were developed at four frequencies: 0.01, 0.1, 1 and 10 MHz. The theoretical estimations were qualitatively in agreement with the experimental findings. Important increments in volumetric inductive phase shift measurements were evident at 0.01MHz in theoretical and experimental observations. The results suggest that the tested technique has the potential to detect pathological conditions in breast tissue associated to cancer by non-invasive monitoring. Further complementary studies are warranted to confirm the observations.
Late regional density changes of the lung after radiotherapy for breast cancer
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Background and purpose: To investigate density changes in lung tissue, 3-4 years after postoperative adjuvant radiotherapy for breast cancer, based on dose dependence and regional differences. Material and methods: Sixty-one breast cancer patients, who had received computed tomography (CT) based postoperative radiotherapy, were included. CT scans were performed 35-51 months after start of radiotherapy. Dose information and CT scans from before and after radiotherapy were geometrically aligned in order to analyse changes in air-filled fraction (derived from CT density) as a function of dose for different regions of the lung. Results: Dose-dependent reduction of the air-filled fraction was shown to vary between the different regions of the lung. For lung tissue receiving about 50 Gy, the largest reduction in air-filled fraction was found in the cranial part of the lung. An increased air-filled fraction was observed for lung tissue irradiated to doses below 20 Gy, indicating compensatory response. Conclusions: The treatment-induced change in whole-lung density is a weighted response, involving the different regions, the irradiated volumes, and dose levels to these volumes. Simplistic models may therefore not be appropriate for describing the whole-lung dose-volume-response relationship following inhomogeneous irradiation
Gabrielson, Marike; Chiesa, Flaminia; Paulsson, Janna; Strell, Carina; Behmer, Catharina; Rönnow, Katarina; Czene, Kamila; Östman, Arne; Hall, Per
2016-07-01
Following female sex and age, mammographic density is considered one of the strongest risk factors for breast cancer. Despite the association between mammographic density and breast cancer risk, little is known about the underlying histology and biological basis of breast density. To better understand the mechanisms behind mammographic density we assessed morphology, proliferation and hormone receptor status in relation to mammographic density in breast tissues from healthy women. Tissues were obtained from 2012-2013 by ultrasound-guided core needle biopsy from 160 women as part of the Karma (Karolinska mammography project for risk prediction for breast cancer) project. Mammograms were collected through routine mammography screening and mammographic density was calculated using STRATUS. The histological composition, epithelial and stromal proliferation status and hormone receptor status were assessed through immunohistochemical staining. Higher mammographic density was significantly associated with a greater proportion of stromal and epithelial tissue and a lower proportion of adipose tissue. Epithelial expression levels of Ki-67, oestrogen receptor (ER) and progesterone receptor (PR) were not associated with mammographic density. Epithelial Ki-67 was associated with a greater proportion of epithelial tissue, and epithelial PR was associated with a greater proportion of stromal and a lower proportion of adipose tissue. Epithelial ER was not associated with any tissues. In contrast, expression of ER in the stroma was significantly associated with a greater proportion of stroma, and negatively associated with the amount of adipose tissue. High mammographic density is associated with higher amount of stroma and epithelium and less amount of fat, but is not associated with a change in epithelial proliferation or receptor status. Increased expressions of both epithelial PR and stromal ER are associated with a greater proportion of stroma, suggesting hormonal involvement
Study of the effect of breast tissue density on detection of masses in mammograms.
García-Manso, A; García-Orellana, C J; González-Velasco, H M; Gallardo-Caballero, R; Macías-Macías, M
2013-01-01
One of the parameters that are usually stored for mammograms is the BI-RADS density, which gives an idea of the breast tissue composition. In this work, we study the effect of BI-RADS density in our ongoing project for developing an image-based CAD system to detect masses in mammograms. This system consists of two stages. First, a blind feature extraction is performed for regions of interest (ROIs), using Independent Component Analysis (ICA). Next, in the second stage, those features form the input vectors to a classifier, neural network, or SVM classifier. To train and test our system, the Digital Database for Screening Mammography (DDSM) was used. The results obtained show that the maximum variation in the performance of our system considering only prototypes obtained from mammograms with a concrete value of density (both for training and test) is about 7%, yielding the best values for density equal to 1, and the worst for density equal to 4, for both classifiers. Finally, with the overall results (i.e., using prototypes from mammograms with all the possible values of densities), we obtained a difference in performance that is only 2% lower than the maximum, also for both classifiers. PMID:23573165
Bayesian Approaches to Non-parametric Estimation of Densities on the Unit Interval
Song Li; Silvapulle, Mervyn J.; Param Silvapulle; Xibin Zhang
2012-01-01
This paper investigates nonparametric estimation of density on [0,1]. The kernel estimator of density on [0,1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0,1]. The simulation and ...
Glycemic index, glycemic load and mammographic breast density: the EPIC Florence longitudinal study.
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Giovanna Masala
Full Text Available A few studies have evaluated the association between diet and mammographic breast density (MBD and results are inconsistent. MBD, a well-recognized risk factor for breast cancer, has been proposed as a marker of cumulative exposure to hormones and growth factors. Diets with a high glycemic index (GI or glycemic load (GL may increase breast cancer risk, via an effect on the insulin-like growth factor axis. We have investigated the association between carbohydrate intake, GI, GL and MBD in a prospective study. We identified a large series of women, in the frame of the EPIC-Florence cohort, with a mammogram taken five years after enrolment, when detailed information on dietary and lifestyle habits and anthropometric measurements had been collected. Mammograms have been retrieved (1,668, 83% and MBD assessed according to Wolfe's classification. We compared women with high MBD (P2+DY Wolfe's categories with those with low MBD (N1+P1 through logistic models adjusted for age, education, body mass index, menopause, number of children, breast feeding, physical activity, non-alcohol energy, fibers, saturated fat and alcohol. A direct association between GL and high MBD emerged in the highest quintile of intake in comparison with the lowest quintile (OR = 1.73, 95%CI 1.13-2.67, p for trend = 0.048 while no association with glycemic index was evident. These results were confirmed after exclusion of women reporting to be on a diet or affected with diabetes, and when Hormone Replacement Therapy at the date of mammographic examination used to assess MBD was considered. The effect was particularly evident among leaner women, although no interaction was found. A positive association was suggested for increasing simple sugar and total carbohydrates intakes limited to the highest quintiles. In this Italian population we observed an association between glycemic load, total and rapidly absorbed carbohydrates and high MBD. These novel results warrant further
Institute of Scientific and Technical Information of China (English)
张路平; 王鲁平; 李飚; 赵明
2015-01-01
In order to improve the performance of the probability hypothesis density (PHD) algorithm based particle filter (PF) in terms of number estimation and states extraction of multiple targets, a new probability hypothesis density filter algorithm based on marginalized particle and kernel density estimation is proposed, which utilizes the idea of marginalized particle filter to enhance the estimating performance of the PHD. The state variables are decomposed into linear and non-linear parts. The particle filter is adopted to predict and estimate the nonlinear states of multi-target after dimensionality reduction, while the Kalman filter is applied to estimate the linear parts under linear Gaussian condition. Embedding the information of the linear states into the estimated nonlinear states helps to reduce the estimating variance and improve the accuracy of target number estimation. The meanshift kernel density estimation, being of the inherent nature of searching peak value via an adaptive gradient ascent iteration, is introduced to cluster particles and extract target states, which is independent of the target number and can converge to the local peak position of the PHD distribution while avoiding the errors due to the inaccuracy in modeling and parameters estimation. Experiments show that the proposed algorithm can obtain higher tracking accuracy when using fewer sampling particles and is of lower computational complexity compared with the PF-PHD.
Lindström, Sara; Thompson, Deborah J.; Paterson, Andrew D.; Li, Jingmei; Gierach, Gretchen L.; Scott, Christopher; Stone, Jennifer; Douglas, Julie A.; dos-Santos-Silva, Isabel; Fernandez-Navarro, Pablo; Verghase, Jajini; Smith, Paula; Brown, Judith; Luben, Robert; Wareham, Nicholas J.; Loos, Ruth J.F.; Heit, John A.; Pankratz, V. Shane; Norman, Aaron; Goode, Ellen L.; Cunningham, Julie M.; deAndrade, Mariza; Vierkant, Robert A.; Czene, Kamila; Fasching, Peter A.; Baglietto, Laura; Southey, Melissa C.; Giles, Graham G.; Shah, Kaanan P.; Chan, Heang-Ping; Helvie, Mark A.; Beck, Andrew H.; Knoblauch, Nicholas W.; Hazra, Aditi; Hunter, David J.; Kraft, Peter; Pollan, Marina; Figueroa, Jonine D.; Couch, Fergus J.; Hopper, John L.; Hall, Per; Easton, Douglas F.; Boyd, Norman F.; Vachon, Celine M.; Tamimi, Rulla M.
2015-01-01
Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5×10−8) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B, SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23, TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease susceptibility loci. PMID:25342443
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Shin, Sung Ui; Chang, Jung Min; Bae, Min Sun; Lee, Su Hyun; Cho, Nariya; Seo, Mirinae; Kim, Won Hwa; Moon, Woo Kyung [Seoul National University Hospital, Department of Radiology, Seoul (Korea, Republic of)
2015-01-15
To compare the average glandular dose (AGD) and diagnostic performance of mediolateral oblique (MLO) digital breast tomosynthesis (DBT) plus cranio-caudal (CC) digital mammography (DM) with two-view DM, and to evaluate the correlation of AGD with breast thickness and density. MLO and CC DM and DBT images of both breasts were obtained in 149 subjects. AGDs of DBT and DM per exposure were recorded, and their correlation with breast thickness and density were evaluated. Paired data of MLO DBT plus CC DM and two-view DM were reviewed for presence of malignancy in a jack-knife alternative free-response ROC (JAFROC) method. The AGDs of both DBT and DM, and differences in AGD between DBT and DM (ΔAGD), were correlated with breast thickness and density. The average JAFROC figure of merit (FOM) was significantly higher on the combined technique than two-view DM (P = 0.005). In dense breasts, the FOM and sensitivity of the combined technique was higher than that of two-view DM (P = 0.003) with small ΔAGD. MLO DBT plus CC DM provided higher diagnostic performance than two-view DM in dense breasts with a small increase in AGD. (orig.)
Functional regression approximate Bayesian computation for Gaussian process density estimation
RODRIGUES G.S.; Nott, David J.; Sisson, S. A.
2014-01-01
We propose a novel Bayesian nonparametric method for hierarchical modelling on a set of related density functions, where grouped data in the form of samples from each density function are available. Borrowing strength across the groups is a major challenge in this context. To address this problem, we introduce a hierarchically structured prior, defined over a set of univariate density functions, using convenient transformations of Gaussian processes. Inference is performed through approximate...
Simulation study of diffuse photon density waves traveling through normal and abnormal breast tissue
Deng, Xiaoyuan; Xing, Da
1999-09-01
Diffuse Photon Density Waves (DPDW) is new concept and principle, which takes advantage of the difference of absorption and scattering coefficients of different tissues to study the law of photon density fluctuation during a modulated light traveling through the tissues, thus to explore the structure and function of tissues. With the combination of image reconstruction technology, we can directly `visualize' the tissues. As a non- invasive exam, it has highly extensive applied prospect in medical field and brain cognition study. In this paper, the behavior of DPDW traveling through simulated breast tissue is tentatively examined. Under various conditions, we observed the characteristics of DPDW. We observed the reasonability of the distribution of sources and detectors, the factors that influence the distortion of DPDW. Simulation results could be used as a good theoretical guideline for experiments.
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This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of MGD to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9 ± 4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4 ± 6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum–minimum) of MGD from dedicated breast CT was lower than
Vedantham, Srinivasan; Shi, Linxi; Karellas, Andrew; O'Connell, Avice M.; Conover, David L.
2013-11-01
This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of MGD to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9 ± 4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4 ± 6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum-minimum) of MGD from dedicated breast CT was lower than
Pilot study of bone mineral density in breast cancer patients treated with adjuvant chemotherapy
Headley, J. A.; Theriault, R. L.; LeBlanc, A. D.; Vassilopoulou-Sellin, R.; Hortobagyi, G. N.
1998-01-01
The objective of this cross-sectional study was to determine lumbar spine bone mineral density (BMD) in breast cancer patients previously treated with adjuvant chemotherapy. Sixteen of 27 patients who received adjuvant chemotherapy became permanently amenorrheic as a result of chemotherapy. BMD was measured at the lumbar spine using dual energy X-ray absorptiometry (DEXA). Chemotherapy drugs and dosages along with a history of risk factors for reduced bone density including activity level, tobacco and/or alcohol use, metabolic bone disease, family history, and hormone exposure were identified. Results showed that women who became permanently amenorrheic as a result of chemotherapy had BMD 14% lower than women who maintained menses after chemotherapy. Chemotherapy-treated women who maintained ovarian function had normal BMD. This study suggests that women who have premature menopause as a result of chemotherapy for breast cancer are at increased risk of bone loss and may be at risk for early development of osteoporosis. Women who maintain menses do not appear to be at risk for accelerated trabecular bone loss.
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Tadayyon, Hadi [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Sadeghi-Naini, Ali; Czarnota, Gregory, E-mail: Gregory.Czarnota@sunnybrook.ca [Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 2M9 (Canada); Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada); Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario M5T 1P5 (Canada); Wirtzfeld, Lauren [Department of Physics, Ryerson University, Toronto, Ontario M5B 2K3 (Canada); Wright, Frances C. [Division of Surgical Oncology, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5 (Canada)
2014-01-15
Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor
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Purpose: Tumor grading is an important part of breast cancer diagnosis and currently requires biopsy as its standard. Here, the authors investigate quantitative ultrasound parameters in locally advanced breast cancers that can potentially separate tumors from normal breast tissue and differentiate tumor grades. Methods: Ultrasound images and radiofrequency data from 42 locally advanced breast cancer patients were acquired and analyzed. Parameters related to the linear regression of the power spectrum—midband fit, slope, and 0-MHz-intercept—were determined from breast tumors and normal breast tissues. Mean scatterer spacing was estimated from the spectral autocorrelation, and the effective scatterer diameter and effective acoustic concentration were estimated from the Gaussian form factor. Parametric maps of each quantitative ultrasound parameter were constructed from the gated radiofrequency segments in tumor and normal tissue regions of interest. In addition to the mean values of the parametric maps, higher order statistical features, computed from gray-level co-occurrence matrices were also determined and used for characterization. Finally, linear and quadratic discriminant analyses were performed using combinations of quantitative ultrasound parameters to classify breast tissues. Results: Quantitative ultrasound parameters were found to be statistically different between tumor and normal tissue (p < 0.05). The combination of effective acoustic concentration and mean scatterer spacing could separate tumor from normal tissue with 82% accuracy, while the addition of effective scatterer diameter to the combination did not provide significant improvement (83% accuracy). Furthermore, the two advanced parameters, including effective scatterer diameter and mean scatterer spacing, were found to be statistically differentiating among grade I, II, and III tumors (p = 0.014 for scatterer spacing, p = 0.035 for effective scatterer diameter). The separation of the tumor
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Electron densities of 33 samples of normal (adipose and fibroglangular) and neoplastic (benign and malignant) human breast tissues were determined through Compton scattering data using a monochromatic synchrotron radiation source and an energy dispersive detector. The area of Compton peaks was used to determine the electron densities of the samples. Adipose tissue exhibits the lowest values of electron density whereas malignant tissue the highest. The relationship with their histology was discussed. Comparison with previous results showed differences smaller than 4%. - Highlights: ► Electron density of normal and neoplastic breast tissues was measured using Compton scattering. ► Monochromatic synchrotron radiation was used to obtain the Compton scattering data. ► The area of Compton peaks was used to determine the electron densities of samples. ► Adipose tissue shows the lowest electron density values whereas the malignant tissue the highest. ► Comparison with previous results showed differences smaller than 4%.
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Purpose: Biologically meaningful predictors for locoregional recurrence (LRR) in patients undergoing breast-conserving surgery (BCS) and radiotherapy (RT) are lacking. Tissue components, including extracellular matrix, could confer resistance to ionizing radiation. Fibroglandular and extracellular matrix components of breast tissue relative to adipose tissue can be quantified by the mammographic breast density (MBD), the proportion of dense area relative to the total breast area on mammography. We hypothesized that the MBD might be a predictor of LRR after BCS and RT for invasive breast cancer. Methods and Materials: We conducted a nested case-control study of 136 women with invasive breast cancer who had undergone BCS and RT and had had the MBD ascertained before, or at, diagnosis. Women with known recurrence were matched to women without recurrence by year of diagnosis. The median follow-up was 7.7 years. The percentage of MBD was measured using a computer-based threshold method. Results: Patients with a high MBD (≥75% density) vs. low (≤25%) were at increased risk of LRR (hazard ratio, 4.30; 95% confidence interval, 0.88-021.0; p = 0.071) but not distant recurrence. In addition, we found a complete inverse correlation between high MBD and obesity (body mass index, ≥30 kg/m2). In a multivariate Cox proportional hazards model, patients with MBD in the greatest quartile were at significantly greater risk of LRR (hazard ratio, 6.6; 95% confidence interval, 1.6-27.7; p = 0.01). Obesity without a high MBD also independently predicted for LRR (hazard ratio, 19.3; 95% confidence interval, 4.5-81.7; p < 0.001). Conclusion: The results of our study have shown that a high MBD and obesity are significant independent predictors of LRR after BCS and RT for invasive breast cancer. Additional studies are warranted to validate these findings
Breast density and polymorphisms in genes coding for CYP1A2 and COMT: the Multiethnic Cohort
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Maskarinec Gertraud
2007-02-01
Full Text Available Abstract Background Mammographic density is a strong predictor of breast cancer risk and is increased by hormone replacement therapy (HRT. Some associations with genetic polymorphisms in enzymes involved in estrogen metabolism have been described. This cross-sectional analysis examined the relation between mammographic density and the CYP1A2*1F and COMT Val58 Met polymorphisms among 332 breast cancer cases and 254 controls in the Hawaii component of the Multiethnic Cohort. Methods Mammographic density, before diagnosis in cases, was quantified by using a validated computer-assisted method. Blood samples were genotyped by standard PCR/RFLP methods. Adjusted mean percent density was calculated by genotype using mixed models with the unstructured covariance option. Results A positive association between the C allele in the CYP1A2*1F gene and percent density, but not the dense area, was suggested (p = 0.11. The relation was limited to controls (p = 0.045, postmenopausal women not using HRT (p = 0.08, and normal weight subjects (p = 0.046. We did not observe any relation between the COMT Val58 Met polymorphism and breast density. Conclusion The lack of an association between the CYP1A2 genotype and the size of the dense areas suggests an effect on the non-dense, i.e., fatty breast tissue. The discrepancies among studies may be due to differential susceptibility; changes in enzyme activity as a result of the CYP1A2*1F polymorphism may influence breast tissue differently depending on hormonal status. Larger studies with the ability to look at interactions would be useful to elucidate the influence of genetic variation in CYP1A2 and COMT on the risk of developing breast cancer.
EuroMInd-D: A density estimate of monthly gross domestic product for the euro area
Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi
2015-01-01
EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of a set of coincident time series handling mixed frequencies of observation and ragged–edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a boo...
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Hendra Gunawan
2014-06-01
Full Text Available http://dx.doi.org/10.17014/ijog.vol3no3.20084The precision of topographic density (Bouguer density estimation by the Nettleton approach is based on a minimum correlation of Bouguer gravity anomaly and topography. The other method, the Parasnis approach, is based on a minimum correlation of Bouguer gravity anomaly and Bouguer correction. The precision of Bouguer density estimates was investigated by both methods on simple 2D syntetic models and under an assumption free-air anomaly consisting of an effect of topography, an effect of intracrustal, and an isostatic compensation. Based on simulation results, Bouguer density estimates were then investigated for a gravity survey of 2005 on La Soufriere Volcano-Guadeloupe area (Antilles Islands. The Bouguer density based on the Parasnis approach is 2.71 g/cm3 for the whole area, except the edifice area where average topography density estimates are 2.21 g/cm3 where Bouguer density estimates from previous gravity survey of 1975 are 2.67 g/cm3. The Bouguer density in La Soufriere Volcano was uncertainly estimated to be 0.1 g/cm3. For the studied area, the density deduced from refraction seismic data is coherent with the recent Bouguer density estimates. New Bouguer anomaly map based on these Bouguer density values allows to a better geological intepretation.
Estimation of the cost of treatment by chemotherapy for early breast cancer in Morocco
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Boutayeb Saber
2010-09-01
Full Text Available Abstract Background Breast cancer is the first cancer in women both in incidence and mortality. The treatment of breast cancer benefited from the progress of chemotherapy and targeted therapies, but there was a parallel increase in treatment costs. Despite a relatively high incidence of many sites of cancer, so far, there is no national register for this disease in Morocco. The main goal of this paper is to estimate the total cost of chemotherapy in the early stages of breast cancer due to its frequency and the chances of patients being cured. This study provides health decision-makers with a first estimate of costs and the opportunity to achieve the optimal use of available data to estimate the needs of antimitotics and trastuzumab in Morocco. Method We start by evaluating the individual cost according to the therapeutic sub-groups, namely: 1. Patients needing chemotherapy with only anthracycline-based therapy. 2. Patients needing chemotherapy with both anthracycline and taxane but without trastuzumab. 3. Patients needing trastuzumab in addition to chemotherapy. For each sub-group, the protocol of treatment is described, and the individual costs per unit, and for the whole cycle, are evaluated. Then we estimate the number of women suffering from breast cancer on the basis of two data bases available in Morocco. Finally, we calculate the total annual cost of treatment of breast cancer in Morocco. Results The total cost of breast cancer in Morocco is given in Moroccan dirhams (MAD, the US dollar at the current exchange rate (MAD 10 = USD 1.30 and in international dollars or purchasing power parity (MAD 10 = PPP 1.95. The cost of a therapy with trastuzumab is 8.4 times the cost of a sequential chemotherapy combining anthracycline and taxane, and nearly 60 times the cost of chemotherapy based on anthracycline alone. Globally, between USD 13.3 million and USD 28.6 million need to be devoted every year by the Moroccan health authorities to treat
Dorgan, Joanne F.; Liu, Lea; Klifa, Catherine; Hylton, Nola; Shepherd, John A.; Stanczyk, Frank Z.; Snetselaar, Linda G.; Van Horn, Linda; Stevens, Victor J.; Robson, Alan; Kwiterovich, Peter O.; Lasser, Norman L.; Himes, John H.; Gabriel, Kelley Pettee; Kriska, Andrea; Ruder, Elizabeth H.; Fang, Carolyn Y.; Barton, Bruce A.
2010-01-01
Background Adolescent diet is hypothesized to influence breast cancer risk. We evaluated the long-term effects of an intervention to lower fat intake among adolescent girls on biomarkers that are related to breast cancer risk in adults. Methods A follow-up study was conducted of 230 girls who participated in the Dietary Intervention Study in Children (DISC), in which healthy, prepubertal 8-10 year olds were randomly assigned to usual care or to a behavioral intervention that promoted a reduced fat diet. Participants were 25-29 years old at follow-up visits. All tests of statistical significance are two-sided. Results In analyses that did not take account of diet at the time of the follow-up visit, the only statistically significant treatment group difference was higher bone mineral content (BMC) in intervention group participants compared to usual care group participants; their mean BMCs were 2,444g and 2,377g, respectively. After adjustment for current diet, the intervention group also had statistically significantly higher bone mineral density and luteal phase serum estradiol concentrations. Serum progesterone concentrations and breast density did not differ by treatment group in unadjusted or adjusted analyses. Conclusion Results do not support the hypothesis that consumption of a lower fat diet during adolescence reduces breast cancer risk via effects on subsequent serum estradiol and progesterone levels, breast density or BMD. Impact Additional research is needed to clarify the association of adolescent diet with breast cancer risk and to determine if the results reported here are specific to the DISC intervention or more broadly applicable. PMID:20501774
Sandhu, Narinder; Schetter, Susann E; Liao, Jason; Hartman, Terryl J; Richie, John P; McGinley, John; Thompson, Henry J; Prokopczyk, Bogdan; DuBrock, Cynthia; Signori, Carina; Hamilton, Christopher; Calcagnotto, Ana; Trushin, Neil; Aliaga, Cesar; Demers, Laurence M; El-Bayoumy, Karam; Manni, Andrea
2016-04-01
Preclinical data indicate that omega-3 fatty acids (n-3FA) potentiate the chemopreventive effect of the antiestrogen (AE) tamoxifen against mammary carcinogenesis. The role of n-3FA in breast cancer prevention in humans is controversial. Preclinical and epidemiologic data suggest that n-3FA may be preferentially protective in obese subjects. To directly test the protective effect of n-3FA against breast cancer, we conducted a 2-year, open-label randomized clinical trial in 266 healthy postmenopausal women (50% normal weight, 30% overweight, 20% obese) with high breast density (BD; ≥25%) detected on their routine screening mammograms. Eligible women were randomized to one of the following five groups (i) no treatment, control; (ii) raloxifene 60 mg; (iii) raloxifene 30 mg; (iv) n-3FA lovaza 4 g; and (v) lovaza 4 g plus raloxifene 30 mg. The 2-year change in BD, a validated biomarker of breast cancer risk, was the primary endpoint of the study. In subset analysis, we tested the prespecified hypothesis that body mass index (BMI) influences the relationship between plasma n-3FA on BD. While none of the interventions affected BD in the intention-to-treat analysis, increase in plasma DHA was associated with a decrease in absolute breast density but only in participants with BMI >29. Our results suggest that obese women may preferentially experience breast cancer risk reduction from n-3FA administration.Cancer Prev Res; 9(4); 275-82. ©2015 AACR. PMID:26714774
Directory of Open Access Journals (Sweden)
Kirsten Knutson, MPH
2008-01-01
Full Text Available Introduction Populations eligible for public health programs are often narrowly defined and, therefore, difficult to describe quantitatively, particularly at the local level, because of lack of data. This information, however, is vital for program planning and evaluation. We demonstrate the application of a statistical method using multiple sources of data to generate county estimates of women eligible for free breast cancer screening and diagnostic services through California’s Cancer Detection Programs: Every Woman Counts.MethodsWe used the small-area estimation method to determine the proportion of eligible women by county and racial/ethnic group. To do so, we included individual and community data in a generalized, linear, mixed-effect model.ResultsOur method yielded widely varied estimated proportions of service-eligible women at the county level. In all counties, the estimated proportion of eligible women was higher for Hispanics than for whites, blacks, Asian/Pacific Islanders, or American Indian/Alaska Natives. Across counties, the estimated proportions of eligible Hispanic women varied more than did those of women of other races.ConclusionThe small-area estimation method is a powerful tool for approximating narrowly defined eligible or target populations that are not represented fully in any one data source. The variability and reliability of the estimates are measurable and meaningful. Public health programs can use this method to estimate the size of local populations eligible for, or in need of, preventive health services and interventions.
Estimation of current density distribution under electrodes for external defibrillation
Directory of Open Access Journals (Sweden)
Papazov Sava P
2002-12-01
Full Text Available Abstract Background Transthoracic defibrillation is the most common life-saving technique for the restoration of the heart rhythm of cardiac arrest victims. The procedure requires adequate application of large electrodes on the patient chest, to ensure low-resistance electrical contact. The current density distribution under the electrodes is non-uniform, leading to muscle contraction and pain, or risks of burning. The recent introduction of automatic external defibrillators and even wearable defibrillators, presents new demanding requirements for the structure of electrodes. Method and Results Using the pseudo-elliptic differential equation of Laplace type with appropriate boundary conditions and applying finite element method modeling, electrodes of various shapes and structure were studied. The non-uniformity of the current density distribution was shown to be moderately improved by adding a low resistivity layer between the metal and tissue and by a ring around the electrode perimeter. The inclusion of openings in long-term wearable electrodes additionally disturbs the current density profile. However, a number of small-size perforations may result in acceptable current density distribution. Conclusion The current density distribution non-uniformity of circular electrodes is about 30% less than that of square-shaped electrodes. The use of an interface layer of intermediate resistivity, comparable to that of the underlying tissues, and a high-resistivity perimeter ring, can further improve the distribution. The inclusion of skin aeration openings disturbs the current paths, but an appropriate selection of number and size provides a reasonable compromise.
Directory of Open Access Journals (Sweden)
Rongda Chen
Full Text Available Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk. The study introduces two kinds of models of distribution, Beta distribution estimation and kernel density distribution estimation, to simulate the distribution of recovery rates of corporate loans and bonds. As is known, models based on Beta distribution are common in daily usage, such as CreditMetrics by J.P. Morgan, Portfolio Manager by KMV and Losscalc by Moody's. However, it has a fatal defect that it can't fit the bimodal or multimodal distributions such as recovery rates of corporate loans and bonds as Moody's new data show. In order to overcome this flaw, the kernel density estimation is introduced and we compare the simulation results by histogram, Beta distribution estimation and kernel density estimation to reach the conclusion that the Gaussian kernel density distribution really better imitates the distribution of the bimodal or multimodal data samples of corporate loans and bonds. Finally, a Chi-square test of the Gaussian kernel density estimation proves that it can fit the curve of recovery rates of loans and bonds. So using the kernel density distribution to precisely delineate the bimodal recovery rates of bonds is optimal in credit risk management.
An evidence-based estimate of appropriate radiotherapy utilization rate for breast cancer
International Nuclear Information System (INIS)
Purpose: Current estimates of the proportion of cancer patients who will require radiotherapy (RT) are based almost entirely on expert opinion. We sought to use an evidence-based approach to estimate the proportion of incident cases of breast cancer that will require RT at any point in the evolution of the illness. Methods and Materials: We undertook a systematic review of the literature to identify indications for RT for breast cancer and to ascertain the level of evidence that supported each indication. An epidemiologic approach was then used to estimate the incidence of each indication for RT in a typical North American population of breast cancer patients. The effect of sampling error on the estimated appropriate rate of RT was calculated mathematically, and the effect of systematic error was estimated by sensitivity analysis. Results: It was estimated that 66.4% ± 4.8% of breast cancer patients develop one or more indications for RT at some point in the course of the illness. The plausible range for this rate was 56.3%-72.4% on sensitivity analysis. Of all breast cancer patients, 57.3% ± 4.7% require RT in their initial treatment and 9.1% ± 1.0% do so later for recurrence or progression. The proportion of patients who ever require RT is stage dependent: 39.8% ± 1.1% in ductal carcinoma in situ; 68.6% ± 4.1% in Stage I invasive carcinoma; 81.5% ± 2.3% in Stage II; 95.3% ± 0.3% in Stage III; and 63.7% ± 0.3% in Stage IV. Conclusion: This method provides a rational starting point for the long-term planning of RT services and for the audit of access to RT at the population level. By completing such evaluations in the major cancer sites, it will be possible to estimate the appropriate RT treatment rate for the cancer population as a whole
Energy Technology Data Exchange (ETDEWEB)
Kim, Eun Kyung; Lee, Yong Hee; Son, Hong Ju; Oh, Ki Keun; Chung, Hyun Cheol; Lee, Kyong Sik [Yonsei University College of Medicine, Seoul (Korea, Republic of)
2000-12-15
To evaluate how breast cancer vascularity detected by power Doppler sonography correlates with microvessel density(MVD) and lymph node involvement. Power Doppler US was performed on 47 patients with pathologically diagnosed invasive ductal carcinoma. According to the presense or absence of vessels, power Doppler findings were categorized regarding total tumors and tumors less than 2 cm. MVD was assessed immunohistochemically using polyclonal antisera against factor VIII. Tumor vascularity was correlated with MVD and lymph node involvement. Among 47 infiltrating ductal carcinomas, 35 (74.5%) cases were vascular and 12 (25.5%) cases were avascular on power Doppler US. The mean MVD of the vascular and avascular carcinomas did not show any statistical difference. However, lymph mode involvement showed significant statistical difference between the two groups (51.4% versus 25.0%, p=0.036), even though in cancers less than 2 cm (40% versus 22.2%, p=0.047). Breast cancer vascularity detected by power Doppler sonography was not correlated with MVD but correlated with lymph node involvement. So we suggest that power Doppler sonography may be useful for predicting lymph node metastasis.
International Nuclear Information System (INIS)
In Japan it is considered that mammography should be introduced with physical examination for the mass screening of breast cancer instead of physical examination alone, which is performed at present. Before the introduction of mammography, a mathematical simulation should be performed to show the reduction in breast cancer mortality by mass screening compared with an unscreened population. A mathematical model of cancer screening devised by the authors was used to estimate the number of deaths due to breast cancer (A) in the screened group and those (B) in the unscreened group within the same population. Then the relative risk (RR) and attributable risk (RD) were calculated as (A/B) and (B-A) respectively. Three methods of mass screening were compared: (1) physical examination (1-year interval), (2) mammography with physical examination (1-year interval), (3) mammography with physical examination (2-year interval). The calculated RR values were 0.85 for (1), 0.60 for (2) and 0.69 for (3). Assuming that the incidence of breast cancer was 100/105 person-years, the calculated RD values were 3.0, 8.1 and 6.2 persons/105 person-years for (1), (2) and (3), respectively. The 95% confidence interval of RR for three methods was over 1.0, and thus the reduction of breast cancer mortality was not statistically significant in the present population. In conclusion, mammography with physical examination may reduce breast cancer mortality in comparison with physical examination alone, but a larger number of women must be screened in order to obtain a significant RR value. (author)
Huerga, Iker; Gerrikagoitia, Jon Kepa
2010-01-01
Risk estimation of developing breast cancer poses as the first prevention method for early diagnosis. Furthermore, data integration from different departments involved in the process plays a key role. In order to guarantee patient safety, the whole process should be orchestrated and monitored automatically. Support for the solution will be a linked data cloud, composed by all the departments that take part in the process, combined with rule engines.
Estimation of Ga-67 radiation dose to a breast-fed infant
International Nuclear Information System (INIS)
Full text: The quality assurance programs for the practice of nuclear medicine in Colombia include optimization of public exposure by the radioactive sources used in medical diagnosis and treatment. Precautionary measures notwithstanding, occasionally members of the public receive doses larger than expected; usually there is no direct data to evaluate dose. We briefly describe the process to estimate the radiation dose absorbed by a 5-month-old baby that was inadvertently breast-fed for 48 hours by his 22-year-old mother that was administered 296 MBq of radioactive Ga-67 citrate. After the intravenous administration, the Ga-67 is commonly observed in the intestine, and other organs, and in the breasts of lactating women, thus possibly leading to radiation exposure of the infant's lower intestine. We had 256x256 single photon emission computed tomography (SPECT) images, and whole-body 1024 x 256 planar images, taken 48h and 72 h after Ga-67 intake. The images were obtained with a Siemens E-cam gamma camera, a 20% energy window was placed at the 93, 184 and 296 keV gamma photopeaks. From these images we calculated the concentration of Ga-67 in mother's milk (using Medical Internal Radiation Dose MIRD methodology). Hence, the dose absorbed by the baby. The radioactivity in breast milk per liter was 4% of the injected activity. The dose absorbed by the infant's lower intestine was 11 mGy. The effective dose to the infant was estimated as 7 mSv, which is above the annual limit to the general public (1 mSv/year). Hence, an infant breast-fed by a mother undergoing Ga-67 treatment may easily receive a radiation dose in excess of the annual upper limit. From the viewpoint of radiation protection it is extremely important to convey to the mother the necessity of abiding by the standard medical recommendation of discontinuing breast feeding for at least 2 weeks after Ga-67 intake. (author)
Change in bone mineral density during adjuvant chemotherapy for early-stage breast cancer
DEFF Research Database (Denmark)
Christensen, Carina Ørts; Cronin-Fenton, Deirdre; Frøslev, Trine;
2016-01-01
PURPOSE: Adjuvant chemotherapy has been associated with loss of bone mineral density (BMD) either as a direct effect or due to glucocorticoids used as supportive care medication. A prospective cohort study was conducted to evaluate changes in BMD from baseline to right after completion of...... chemotherapy, i.e., 4 months. METHODS: Dual-imaging X-ray absorptiometry (DXA) was performed at baseline and after completing anthracycline- and taxane-based chemotherapy to measure BMD in the spine, hip, and forearm in early-stage breast cancer patients. High-dose prednisolone was used at three weekly...... % CI -3.3; -0.1, p = 0.04) compared to never/former smokers. CONCLUSIONS: Adjuvant chemotherapy supplemented with prednisolone was not associated with loss of BMD. Postmenopausal women gained bone mass, whereas current smokers lost bone mass....
DEFF Research Database (Denmark)
Offersen, Birgitte Vrou; Riisbro, Rikke; Knoop, Ann;
2007-01-01
Plasminogen Activator Inhibitor type-1 (PAI-1) is involved in tumor invasion and progression. High levels of PAI-1 are associated with poor prognosis in breast cancer, and PAI-1 has been shown to play a role in angiogenic processes. Since estimates of tumor angiogenesis may predict poor prognosis...... we studied the relationship between PAI-1 and estimates of angiogenesis in breast cancer. Tumor tissue specimens from 438 breast cancer patients were included. Median follow-up was 10.3 years. Protein levels of PAI-1 were measured using an ELISA. Angiogenesis scores were performed using a Chalkley.......009) were independent markers of death from breast cancer. This study confirms high PAI-1 or high Chalkley counts as markers of poor prognosis in breast cancer patients, and suggests that the prognostic impact of PAI-1 is independent of its supposed involvement in tumor angiogenesis. Udgivelsesdato: 2007...
Singh, Harpreet; Arvind; Dorai, Kavita
2016-09-01
Estimation of quantum states is an important step in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not positive, and hence not physically acceptable. How do we ensure that at all stages of reconstruction, we keep the density matrix positive? Recently a method has been suggested based on maximum likelihood estimation, wherein the density matrix is guaranteed to be positive definite. We experimentally implement this protocol on an NMR quantum information processor. We discuss several examples and compare with the standard method of state estimation.
DEFF Research Database (Denmark)
Nielsen, Mads; Raundahl, Jakob; Pettersen, Paola; Loog, Marco; Karemore, Gopal Raghunath; Karsdal, Morten; Christiansen, Claus
2009-01-01
Objective: To investigate whether transdermal low dose estradiol treatment induces changes in mammographic density or heterogeneity compared to raloxifene. Secondarily, if these changes relate to changes in bone formation/resorption markers, and if these findings indicate elevation of breast cancer...
Use of health plan data to estimate cost and outcomes of a breast cancer population
International Nuclear Information System (INIS)
Purpose/Objective: To compare insurance billing data with tumor registry data for estimating date of diagnosis and date of recurrence. To collect and estimate cost of treatment from billing data as a step towards performing cost-effective or cost-utility analysis. To correlate first year treatment cost first year with overall cost to enable the former to serve as a proxy for the latter for patients migrating out of insurance plans. Materials and Methods: Billing data for patients(pts.) diagnosed with breast cancer between 1990-1992 was obtained from Paramount Health Plans, a NCQA accredited health plan in Northwest Ohio. Tumor registry and hospital records were surveyed for the clinical data. Total cost of care received by pts., cost of care associated with treatment of breast cancer, and cost of care billed as breast cancer care was collected for each 12 month period from the date of diagnosis. Costs were measured from a payers, i.e. health plans, perspective. Net present value (NPV) costs discounted at a rate of 3% to the year of diagnosis are reported. Pts. were considered in the plan for the entire duration of the study if they were in the plan from the time of diagnosis to the end of the analysis, (12(96)). Students t-test was used to determined statistical differences between groups analyzed. Results: Paramount Health Plan was a small health plan with approximately 10,000-13,000 female enrolees during the study period. Breast cancer was diagnosed in 21 women during 1990-1992 with 18 pts. diagnosed while in the insurance plan and 3 diagnosed prior to entry into the plan. (12(18)) pts. were in the plan for the entire duration of the study. The mean deviation for the date of diagnosis as recorded from tumor registry data, compared to the first date that a diagnosis of breast cancer appears on the billing record is 18 days (range:0-158). Four pts. experienced a recurrence. A determination of a recurrence from insurance records was only possible in (1(4)) pts. who
Chalkley estimates of angiogenesis in early breast cancer--relevance to prognosis
DEFF Research Database (Denmark)
Offersen, Birgitte V; Sørensen, Flemming Brandt; Yilmaz, Mette; Knoop, Ann; Overgaard, Jens
The aim of this study was to investigate whether Chalkley estimates of angiogenesis add new knowledge regarding prediction of prognosis in 455 consecutive early breast carcinomas, both node-positive (52%) and node-negative (48%). Median follow-up was 101 months. Intense vascularization indicated......, high malignancy grade, negative oestrogen receptor, and increasing Chalkley counts (both tertiles and continuous) were independent markers of disease-specific death. Thus, in a univariate analysis it was found that high Chalkley estimates of angiogenesis indicated a poor prognosis, but high Chalkley...
Carlos B. Kasper; Fábio D. Mazim; José B. G. Soares; Tadeu G. de Oliveira
2015-01-01
ABSTRACT Using camera traps and capture/recapture analyses we recorded the presence and abundance of cat species at Turvo State Park, in southern Brazil. Ocelot [Leopardus pardalis (Linnaeus, 1758)] population density was estimated for two areas of the park, with differing management profiles. Density estimates varied from 0.14 to 0.26 indiv. km2. Another five cat species were recorded at very low frequencies, precluding more accurate analyses. We estimate 24 to 45 ocelots occur in the reserv...
International Nuclear Information System (INIS)
We aimed to determine whether background 18F-FDG uptake in positron emission mammography (PEM) was related to mammographic density or background parenchymal enhancement in breast MRI. Methods: We studied a total of 52 patients (mean age, 50.9 years, 26 premenopausal, 26 postmenopausal) with newly diagnosed breast cancer who underwent 18F-FDG PEM (positron emission mammography), conventional mammography and breast MRI. The background mean 18F-FDG uptake value on PEM was obtained by drawing a user-defined region of interest (ROI) in a normal area of the contralateral breast. We reviewed the mammography retrospectively for overall breast density of contralateral breast according to the four-point scale (grade 1–4) of the Breast Imaging Reporting and Data System (BI-RADS) classification. The background parenchymal enhancement of breast MRI was classified as minimal, mild, moderate, or marked. All imaging findings were interpreted by two readers in consensus without knowledge of image findings of other modalities. Results: Multiple linear regression analysis revealed a significant correlation between background 18F-FDG uptake on PEM and mammographic density after adjustment for age and menopausal status (P 18F-FDG uptake on PEM and background parenchymal enhancement on MRI. Conclusion: Background 18F-FDG uptake on PEM significantly increases as mammographic density increases. Background parenchymal enhancement in breast MRI was not an independent predictor of the background 18F-FDG uptake on PEM unlike mammographic density
Using mortality data to estimate radiation effects on breast cancer incidence
International Nuclear Information System (INIS)
In this paper we combine Japanese data on radiation exposure and cancer mortality with U.S. data on cancer incidence and lethality to estimate the effects of ionizing radiation on cancer incidence. The analysis is based on the mathematical relationship between the mortality rate and the incidence and lethality rates, as well as on statistical models that relate Japanese incidence rates to U.S. incidence rates and radiation risk factors. Our approach assumes that the risk of death from causes other than the cancer does not depend on whether or not the cancer is present, and among individuals with the cancer, the risk of death attributable to the cancer is the same in Japan and the U.S. and is not affected by radiation exposure. In particular, we focus on the incidence of breast cancer in Japanese women and how this incidence is affected by radiation risk factors. The analysis uses Japanese exposure and mortality data from the Radiation Effects Research Foundation study of atomic bomb survivors and U.S. incidence and lethality data from the Surveillance, Epidemiology, and End Results Registry. Even without Japanese incidence data, we obtain reasonable estimates of the incidence of breast cancer in unexposed Japanese women and identify the radiation risk factors that affect this incidence. Our analysis demonstrates that the age at exposure is an important risk factor, but that the incidence of breast cancer is not affected by the city of residence (Nagasaki versus Hiroshima) or the time since exposure
Performances of Different Algorithms for Tracer Kinetics Parameters Estimation in Breast DCE-MRI
Directory of Open Access Journals (Sweden)
Roberta Fusco
2014-07-01
Full Text Available Objective of this study was to evaluate the performances of different algorithms for tracer kinetics parameters estimation in breast Dynamic Contrast Enhanced-MRI. We considered four algorithms: two non-iterative algorithms based on impulsive and linear approximation of the Arterial Input Function respectively; and two iterative algorithms widely used for non-linear regression (Levenberg-Marquardt, LM and VARiable PROjection, VARPRO. Per each value of the kinetic parameters within a physiological range, we simulated 100 noisy curves and estimated the parameters with all algorithms. Sampling time, total duration and noise level have been chosen as in a typical breast examination. We compared the performances with respect to the Cramer-Rao Lower Bound (CRLB. Moreover, in order to gain further insight we applied the algorithms to a real breast examination. Accuracy of all the methods depends on the specific value of the parameters. The methods are in general biased: however, VARPRO showed small bias in a region of the parameter space larger than the other methods; moreover, VARPRO approached CRLB and the number of iterations were smaller than LM. In the specific conditions analyzed, VARPRO showed better performances with respect to LM and to non-iterative algorithms
DEFF Research Database (Denmark)
Hansen, S; Grabau, D A; Rose, C;
1998-01-01
biologic variation among patients was the major contributor to the total variation. The Chalkley and MVD methods have been published to provide significant prognostic estimates in breast cancer, but the Chalkley method has less observer variation and may be superior from a methodologic point of view....
Preoperative TRAM free flap volume estimation for breast reconstruction in lean patients.
Minn, Kyung Won; Hong, Ki Yong; Lee, Sang Woo
2010-04-01
To obtain pleasing symmetry in breast reconstruction with transverse rectus abdominis myocutaneous (TRAM) free flap, a large amount of abdominal flap is elevated and remnant tissue is trimmed in most cases. However, elevation of abundant abdominal flap can cause excessive tension in donor site closure and increase the possibility of hypertrophic scarring especially in lean patients. The TRAM flap was divided into 4 zones in routine manner; the depth and dimension of the 4 zones were obtained using ultrasound and AutoCAD (Autodesk Inc., San Rafael, CA), respectively. The acquired numbers were then multiplied to obtain an estimate of volume of each zone and the each zone volume was added. To confirm the relation between the estimated volume and the actual volume, authors compared intraoperative actual TRAM flap volumes with preoperative estimated volumes in 30 consecutive TRAM free flap breast reconstructions. The estimated volumes and the actual elevated volumes of flap were found to be correlated by regression analysis (r = 0.9258, P AutoCAD (Autodesk Inc.) allow the authors to attain the precise volume desired for elevation. This method provides advantages in terms of minimal flap trimming, easier closure of donor sites, reduced scar widening and symmetry, especially in lean patients. PMID:20224334
Efficient estimation of dynamic density functions with an application to outlier detection
Qahtan, Abdulhakim Ali
2012-01-01
In this paper, we propose a new method to estimate the dynamic density over data streams, named KDE-Track as it is based on a conventional and widely used Kernel Density Estimation (KDE) method. KDE-Track can efficiently estimate the density with linear complexity by using interpolation on a kernel model, which is incrementally updated upon the arrival of streaming data. Both theoretical analysis and experimental validation show that KDE-Track outperforms traditional KDE and a baseline method Cluster-Kernels on estimation accuracy of the complex density structures in data streams, computing time and memory usage. KDE-Track is also demonstrated on timely catching the dynamic density of synthetic and real-world data. In addition, KDE-Track is used to accurately detect outliers in sensor data and compared with two existing methods developed for detecting outliers and cleaning sensor data. © 2012 ACM.
An Efficient Acoustic Density Estimation Method with Human Detectors Applied to Gibbons in Cambodia.
Directory of Open Access Journals (Sweden)
Darren Kidney
Full Text Available Some animal species are hard to see but easy to hear. Standard visual methods for estimating population density for such species are often ineffective or inefficient, but methods based on passive acoustics show more promise. We develop spatially explicit capture-recapture (SECR methods for territorial vocalising species, in which humans act as an acoustic detector array. We use SECR and estimated bearing data from a single-occasion acoustic survey of a gibbon population in northeastern Cambodia to estimate the density of calling groups. The properties of the estimator are assessed using a simulation study, in which a variety of survey designs are also investigated. We then present a new form of the SECR likelihood for multi-occasion data which accounts for the stochastic availability of animals. In the context of gibbon surveys this allows model-based estimation of the proportion of groups that produce territorial vocalisations on a given day, thereby enabling the density of groups, instead of the density of calling groups, to be estimated. We illustrate the performance of this new estimator by simulation. We show that it is possible to estimate density reliably from human acoustic detections of visually cryptic species using SECR methods. For gibbon surveys we also show that incorporating observers' estimates of bearings to detected groups substantially improves estimator performance. Using the new form of the SECR likelihood we demonstrate that estimates of availability, in addition to population density and detection function parameters, can be obtained from multi-occasion data, and that the detection function parameters are not confounded with the availability parameter. This acoustic SECR method provides a means of obtaining reliable density estimates for territorial vocalising species. It is also efficient in terms of data requirements since since it only requires routine survey data. We anticipate that the low-tech field requirements will
DEFF Research Database (Denmark)
Nielsen, Mads; Pettersen, Paola; Alexandersen, P;
2010-01-01
(1 mg) continuously combined with drospirenone (2 mg) was administered to postmenopausal women for up to 2 years (26 treatment cycles, 28 d/cycle) in a randomized, placebo-controlled trial. This post hoc analysis assessed the changes in breast density measured from digitized images by two radiologist...... mineral density at the spine and femur were also assessed. Results: Breast density assessed by the radiologist-based approaches increased significantly from baseline in the HT group (P < 0.01), with significant divergence from placebo at 2 years (P < 0.01). Heterogeneity examination of radiograph score by...... computer-based technique was unchanged in the HT group and decreased significantly with placebo (P < 0.001) to produce a significant group divergence (P < 0.05). Changes in mammographic markers by radiologist- and computer-based approaches correlated with each other in the HT group (P < 0.01) but not in...
Numerical estimate of infinite invariant densities: application to Pesin-type identity
International Nuclear Information System (INIS)
Weakly chaotic maps with unstable fixed points are investigated in the regime where the invariant density is non-normalizable. We propose that the infinite invariant density ρ-bar (x) of these maps can be estimated using ρ-bar (x)= lim t→∞t1-αρ(x,t), in agreement with earlier work of Thaler. Here ρ(x,t) is the normalized density of particles. This definition uniquely determines the infinite density and is a valuable tool for numerical estimations. We use this density to estimate the sub-exponential separation λα of nearby trajectories. For a particular map introduced by Thaler we use an analytical expression for the infinite invariant density to calculate λα exactly, which perfectly matches simulations without fitting. Misunderstanding which recently appeared in the literature is removed. (paper)
Scent Lure Effect on Camera-Trap Based Leopard Density Estimates
Braczkowski, Alexander Richard; Balme, Guy Andrew; Dickman, Amy; Fattebert, Julien; Johnson, Paul; Dickerson, Tristan; MacDonald, David Whyte; Hunter, Luke
2016-01-01
Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of ca...
Hall, Peter
1992-01-01
The bootstrap is a poor estimator of bias in problems of curve estimation, and so bias must be corrected by other means when the bootstrap is used to construct confidence intervals for a probability density. Bias may either be estimated explicitly, or allowed for by undersmoothing the curve estimator. Which of these two approaches is to be preferred? In the present paper we address this question from the viewpoint of coverage accuracy, assuming a given number of derivatives of the unknown den...
International Nuclear Information System (INIS)
Indirect estimation of low-dose radiation hazards is possible using the multihit model of carcinogenesis. This model is based on cancer incidence data collected over many decades on tens of millions of people. Available data on human radiation effects can be introduced into the modeling process without the requirement that these data precisely define the model to be used. This reduction in the information demanded from the limited data on human radiation effects allows a more rational approach to estimation of low-dose radiation hazards and helps to focus attention on research directed towards understanding the process of carcinogenesis, rather than on repeating human or animal experiments that cannot provide sufficient data to resolve the low-dose estimation problem. Assessment of the risk of radiation-induced breast cancer provides an excellent example of the utility of multihit modeling procedures
Montserrat Guillen; Jens Perch Nielsen; Catalina Bolance
2000-01-01
In this paper we concentrate on the estimation of loss functions using nonparametric methods. We focus on the parametric transformation approach to kernel smoothing introduced by Wand, Marron and Ruppert (1991) and compare it with the standard kernel estimator and the multiplicative bias correction method (Hjort and Glad, 1995 and Jones, Linton and Nielsen, 1995). We advocate in this paper that the transformation method behaves excellently when it comes to estimating actuarial and financial l...
Anjali; Deepak
2015-01-01
Breast cancer is the most common site specific cancer in women. Lots of etiological factors have been suggested regarding its causation. The risk is influenced by obesity, parity, exogenous and endogenous hormones, exposure to chemicals and radiation and many more. Various studies suggest that as HDL-C seems to be cardio protective, it is also protective for breast cancer. Serum HDL-C levels are found to be low in breast cancer patients. We studied this hypothesis in local population of South...
EnviroAtlas - Phoenix, AZ - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Austin, TX - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - New Bedford, MA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Portland, OR - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Pittsburgh, PA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Memphis, TN - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Portland, ME - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Des Moines, IA - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Paterson, NJ - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
EnviroAtlas - Tampa, FL - Estimated Intersection Density of Walkable Roads
U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates the intersection density of walkable roads within a 750 meter radius of any given 10 meter pixel in the community. Intersections...
Albada, A.; Dulmen, S. van; Dijkstra, H.; Wieffer, I.; Witkamp, A.; Ausems, M.G.E.M.
2016-01-01
We studied counselees’ expressed understanding of the risk estimate and surveillance recommendation in the final consultation for breast cancer genetic counseling in relation with their risk perception, worry and cancer surveillance adherence 1 year post-counseling. Consecutive counselees were included from 2008 to 2010. Counselees with an indication for diagnostic DNA-testing for themselves or a breast cancer affected relative were requested to complete online questionnaires before and after...
A comparative simulation study of data-driven methods for estimating density level sets
Saavedra-Nieves, Paula; González-Manteiga, Wenceslao; Rodríguez-Casal, Alberto
2014-01-01
Density level sets are mainly estimated using one of three methodologies: plug-in, excess mass, or a hybrid approach. The plug-in methods are based on replacing the unknown density by some nonparametric estimator, usually the kernel. Thus, the bandwidth selection is a fundamental problem from a practical point of view. Recently, specific selectors for level sets have been proposed. However, if some a priori information about the geometry of the level set is available, then excess mass algorit...
Helium beam diagnostics for the estimation electron temperature and density in SST-1
International Nuclear Information System (INIS)
Supersonic helium beam Diagnostics is used to estimate edge electron density and temperature in tokamaks. Ratio of line emission intensities from neutral helium is used to estimate electron temperature and density. Temperature is estimated from the ratio of intensities (728.1 nm /706.3 nm) whereas density is estimated from ratio (668.1 nm/728.1 nm). We have designed and tested a supersonic helium beam injector for edge plasma temperature and density for SST-1 tokamak. The system consists of a supersonic injector and an imaging system. The emission is collected by the imaging system and optical fibers and an EMMCD coupled spectrograph is used to record the spectra from various spatial locations. The spatial resolution is around 5 mm. In a recent campaign in SST-1, we tried to estimate these parameters using the residual helium after the helium GDC. The spectrometer and detection system was calibrated and signal was optimized. The spectra were good enough to use these helium lines to estimate electron temperature and density with an integration time of 10 ms. The observed line ratios are compared with the line ratios obtained from CR model/Atomic Data and Analysis Structure (ADAS) to get an estimate of electron temperature and density. The estimated electron density is in the range of 5 x 1011 - 2 x 1012 cm-3 and electron temperature 30-55 eV. The obtained parameters provide reasonable estimates when compared with other diagnostics considering the diffusion and ionization of neutral helium inside the tokamak. (author)
Novel and simple non-parametric methods of estimating the joint and marginal densities
Alghalith, Moawia
2016-07-01
We introduce very simple non-parametric methods that overcome key limitations of the existing literature on both the joint and marginal density estimation. In doing so, we do not assume any form of the marginal distribution or joint distribution a priori. Furthermore, our method circumvents the bandwidth selection problems. We compare our method to the kernel density method.
International Nuclear Information System (INIS)
OBJECTIVES: To determine the clinical performance of a computer-assisted detection (CAD) system in detecting carcinoma in breasts of different densities. MATERIALS AND METHODS: A total of 264 sets of bilateral screening mammograms taken in craniocaudal and medial-lateral oblique projections during the year 1997 were divided into four groups according to the BI-RADS density classification: fatty (pattern 1), scattered fibroglandular (pattern 2), heterogeneously dense (pattern 3) and extremely dense (pattern 4). Each group contained about 60% normal and 40% biopsy-proven cancer cases. Of the malignant cases, there were a mixture of mammographic findings including focal masses (2.5 cm were not included. The chosen cases were then digitized and analysed by the CAD system. Sensitivity was calculated as detection of cancer by at least one marker in at least one view. Specificity was calculated as the number of false-positive marks per image on normal cases. Statistical tests of significance were performed by using contingency tables and Chi square test. RESULTS: The CAD system detected 14 out of the total 15 cancer cases in totally fatty breasts with a sensitivity of 93.3% at a specificity of 1.3 false-positive marks per image. In breasts with scattered fibroglandular pattern, the sensitivity was 93.9% (31/33) and the specificity was 1.6 false-positive marks per image while in heterogeneously dense breasts, the sensitivity of the CAD system fell to 84.8% at a specificity of 1.6 false-positive marks per image. The sensitivity of the CAD system further dropped to 64.3% in markedly dense breasts while maintaining a specificity of 1.2 false-positive marks per image. The decrease in sensitivity in dense breast was found to be significant (p = 0.046). CONCLUSION: The sensitivity of the CAD system deteriorated significantly as the density of the breast increased while the specificity of the system remained relatively constant. Ho, W. T. and Lam,P.W. (2003). Clinical Radiology58
Energy Technology Data Exchange (ETDEWEB)
Antoniassi, M.; Conceicao, A.L.C. [Departamento de Fisica-Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto-Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo (Brazil); Poletti, M.E., E-mail: poletti@ffclrp.usp.br [Departamento de Fisica-Faculdade de Filosofia Ciencias e Letras de Ribeirao Preto-Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo (Brazil)
2012-07-15
Electron densities of 33 samples of normal (adipose and fibroglangular) and neoplastic (benign and malignant) human breast tissues were determined through Compton scattering data using a monochromatic synchrotron radiation source and an energy dispersive detector. The area of Compton peaks was used to determine the electron densities of the samples. Adipose tissue exhibits the lowest values of electron density whereas malignant tissue the highest. The relationship with their histology was discussed. Comparison with previous results showed differences smaller than 4%. - Highlights: Black-Right-Pointing-Pointer Electron density of normal and neoplastic breast tissues was measured using Compton scattering. Black-Right-Pointing-Pointer Monochromatic synchrotron radiation was used to obtain the Compton scattering data. Black-Right-Pointing-Pointer The area of Compton peaks was used to determine the electron densities of samples. Black-Right-Pointing-Pointer Adipose tissue shows the lowest electron density values whereas the malignant tissue the highest. Black-Right-Pointing-Pointer Comparison with previous results showed differences smaller than 4%.
Estimation of breast dose and cancer risk in chest and abdomen CT procedures
International Nuclear Information System (INIS)
The use of CT in medical diagnosis delivers radiation doses to patents that are higher than those from other radiological procedures. Lack of optimized protocols be an additional source of increased dose in developing countries. The aims of this study are first, to measure patient doses during CT chest and abdomen procedures, second, to estimate the radiation dose to the breast, and third to quantify the radiation risks during the procedures. Patient doses from two common CT examinations were obtained from four hospitals in Khartoum.The patient doses were estimated using measurement of CT dose indexes (CTDI), exposure-related parameters, and the IMPACT spreadsheet based on NRPB conversion factors. A large variation of mean organ doses among hospitals was observed for similar CT examinations. These variations largely originated from different CT scanning protocols used in different hospitals and scanner type. The largest range was found for CT of the chest, for which the dose varied from 2.3 to 47 (average 24.7) mSv and for abdomen CT, it was 1.6 to 18.8 (average 10.2) mSv. Radiation dose to the breast ranged from 1.6 to 32.9 mSv for the chest and 1.1 to 13.2 mSv for the abdomen. The radiation risk per procedure was high. The obtained values were mostly higher than the values of organ doses reported from the other studies. It was concluded that current clinical chest and abdomen protocols result in variable radiation doses to the breast. The magnitude of exposure may have implications for imaging strategies.(Author)
International Nuclear Information System (INIS)
The authors report on a method to calculate radiological risks, applicable to breast screening programs and other controlled medical exposures to ionizing radiation. In particular, it has been applied to make a risk assessment in the Valencian Breast Cancer Early Detection Program (VBCEDP) in Spain. This method is based on a parametric approach, through Markov processes, of hazard functions for radio-induced breast cancer incidence and mortality, with mean glandular breast dose, attained age and age-at-exposure as covariates. Excess relative risk functions of breast cancer mortality have been obtained from two different case-control studies exposed to ionizing radiation, with different follow-up time: the Canadian Fluoroscopy Cohort Study (1950-1987) and the Life Span Study (1950-1985 and 1950-1990), whereas relative risk functions for incidence have been obtained from the Life Span Study (1958-1993), the Massachusetts tuberculosis cohorts (1926-1985 and 1970-1985), the New York post-partum mastitis patients (1930-1981) and the Swedish benign breast disease cohort (1958-1987). Relative risks from these cohorts have been transported to the target population undergoing screening in the Valencian Community, a region in Spain with about four and a half million inhabitants. The SCREENRISK software has been developed to estimate radiological detriments in breast screening. Some hypotheses corresponding to different screening conditions have been considered in order to estimate the total risk associated with a woman who takes part in all screening rounds. In the case of the VBCEDP, the total radio-induced risk probability for fatal breast cancer is in a range between [5 x 10-6, 6 x 10-4] versus the natural rate of dying from breast cancer in the Valencian Community which is 9.2 x 10-3. The results show that these indicators could be included in quality control tests and could be adequate for making comparisons between several screening programs
Energy Technology Data Exchange (ETDEWEB)
Ramos, M [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Ferrer, S [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Villaescusa, J I [Radiation Protection Service, Hospital Universitario La Fe, Avda Campanar, 21 46009 Valencia (Spain); Verdu, G [Chemical and Nuclear Engineering Department, Polytechnic University of Valencia, Camino de Vera s/n 46022 Valencia (Spain); Salas, M D [Public Health General Direction, Conselleria de Sanitat de Valencia, C/Micer Masco, 31 46021 Valencia (Spain); Cuevas, M D [Assistential Service General Direction, Conselleria de Sanitat de Valencia, C/Micer Masco, 31 46021 Valencia (Spain)
2005-02-07
The authors report on a method to calculate radiological risks, applicable to breast screening programs and other controlled medical exposures to ionizing radiation. In particular, it has been applied to make a risk assessment in the Valencian Breast Cancer Early Detection Program (VBCEDP) in Spain. This method is based on a parametric approach, through Markov processes, of hazard functions for radio-induced breast cancer incidence and mortality, with mean glandular breast dose, attained age and age-at-exposure as covariates. Excess relative risk functions of breast cancer mortality have been obtained from two different case-control studies exposed to ionizing radiation, with different follow-up time: the Canadian Fluoroscopy Cohort Study (1950-1987) and the Life Span Study (1950-1985 and 1950-1990), whereas relative risk functions for incidence have been obtained from the Life Span Study (1958-1993), the Massachusetts tuberculosis cohorts (1926-1985 and 1970-1985), the New York post-partum mastitis patients (1930-1981) and the Swedish benign breast disease cohort (1958-1987). Relative risks from these cohorts have been transported to the target population undergoing screening in the Valencian Community, a region in Spain with about four and a half million inhabitants. The SCREENRISK software has been developed to estimate radiological detriments in breast screening. Some hypotheses corresponding to different screening conditions have been considered in order to estimate the total risk associated with a woman who takes part in all screening rounds. In the case of the VBCEDP, the total radio-induced risk probability for fatal breast cancer is in a range between [5 x 10{sup -6}, 6 x 10{sup -4}] versus the natural rate of dying from breast cancer in the Valencian Community which is 9.2 x 10{sup -3}. The results show that these indicators could be included in quality control tests and could be adequate for making comparisons between several screening programs.
Autocorrelation-based estimate of particle image density for diffraction limited particle images
International Nuclear Information System (INIS)
In particle image velocimetry (PIV), the number of particle images per interrogation region, or particle image density, impacts the strength of the correlation and, as a result, the number of valid vectors and the measurement uncertainty. For some uncertainty methods, an a priori estimate of the uncertainty of PIV requires knowledge of the particle image density. An autocorrelation-based method for estimating the local, instantaneous, particle image density is presented. The method assumes that the particle images are diffraction limited and thus Gaussian in shape. Synthetic images are used to develop an empirical relationship between the autocorrelation peak magnitude and the particle image density, particle image diameter, particle image intensity, and interrogation region size. This relationship is tested using experimental images. The experimental results are compared to particle image densities obtained through implementing a local maximum method and are found to be more robust. The effect of varying particle image intensities was also investigated and is found to affect the measurement of the particle image density. Knowledge of the particle image density in PIV facilitates uncertainty estimation, and can alert the user that particle image density is too low or too high, even if these conditions are intermittent. This information can be used as a new vector validation criterion for PIV processing. In addition, use of this method is not limited to PIV, but it can be used to determine the density of any image with diffraction limited particle images. (paper)
Jażdżewska, Iwona
2012-01-01
The article presents the results of the analysis of changes of the urban population density in Central Poland in the 20th century using one of the statistical methods meant for the estimation of discrete distributions, the so-called kernel function, and its brief characteristics. The studies cover the period, for which comparable data has been gathered (from 1931 to 2010). The results of the studies have been presented in a textual form and on 9 drawings, showcasing the chan...
Directory of Open Access Journals (Sweden)
Anjali
2015-12-01
Full Text Available Breast cancer is the most common site specific cancer in women. Lots of etiological factors have been suggested regarding its causation. The risk is influenced by obesity, parity, exogenous and endogenous hormones, exposure to chemicals and radiation and many more. Various studies suggest that as HDL-C seems to be cardio protective, it is also protective for breast cancer. Serum HDL-C levels are found to be low in breast cancer patients. We studied this hypothesis in local population of Southern Rajasthan and nearby region to see if low serum HDL-C is associated with increased risk of breast cancer. We studied serum HDL-C level in 50 female patients of breast cancer along with their menopausal status and compared it to their respective controls. We found that breast cancer patients had significantly low level of serum HDL-C and presented in advanced stage of cancer. It supports that low serum HDL-C level is associated with increased risk of breast cancer. So one should think about those dietary and lifestyle measures, which maintain high serum HDL-C level so that it might become preventive measure for breast cancer.
Woods, Carol M.; Thissen, David
2006-01-01
The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the…
Local linear density estimation for filtered survival data, with bias correction
DEFF Research Database (Denmark)
Nielsen, Jens Perch; Tanggaard, Carsten; Jones, M.C.
2009-01-01
A class of local linear kernel density estimators based on weighted least-squares kernel estimation is considered within the framework of Aalen's multiplicative intensity model. This model includes the filtered data model that, in turn, allows for truncation and/or censoring in addition to accomm...
Pyrethroids in human breast milk: occurrence and nursing daily intake estimation.
Corcellas, Cayo; Feo, Maria Luisa; Torres, Joao Paulo; Malm, Olaf; Ocampo-Duque, William; Eljarrat, Ethel; Barceló, Damià
2012-10-15
There is an assumption that pyrethroid pesticides are converted to non-toxic metabolites by hydrolysis in mammals. However, some recent works have shown their bioaccumulation in human breast milk collected in areas where pyrethroids have been widely used for agriculture or malaria control. In this work, thirteen pyrethroids have been studied in human breast milk samples coming from areas without pyrethroid use for malaria control, such as Brazil, Colombia and Spain. The concentrations of pyrethroids ranged from 1.45 to 24.2 ng g⁻¹ lw. Cypermethrin, λ-cyhalothrin, permethrin and esfenvalerate/fenvalerate were present in all the studied samples. The composition of pyrethroid mixture depended on the country of origin of the samples, bifenthrin being the most abundant in Brazilian samples, λ-cyhalothrin in Colombian and permethrin in Spanish ones. When the pyrethroid concentrations were confronted against the number of gestations, an exponential decay was observed. Moreover, a time trend study was carried out in Brazil, where additional archived pool samples were analyzed, corresponding to years when pyrethroids were applied for dengue epidemic control. In these cases, total pyrethroid levels reached up to 128 ng g⁻¹ lw, and concentrations decreased when massive use was not allowed. Finally, daily intake estimation of nursing infants was calculated in each country and compared to acceptable WHO levels. The estimated daily intakes for nursing infants were always below the acceptable daily intake levels, nevertheless in certain samples the detected concentrations were very close to the maximum acceptable levels. PMID:22717642
Makeev, Andrey; Clajus, Martin; Snyder, Scott; Wang, Xiaolang; Glick, Stephen J
2015-04-01
Semiconductor photon-counting detectors based on high atomic number, high density materials [cadmium zinc telluride (CZT)/cadmium telluride (CdTe)] for x-ray computed tomography (CT) provide advantages over conventional energy-integrating detectors, including reduced electronic and Swank noise, wider dynamic range, capability of spectral CT, and improved signal-to-noise ratio. Certain CT applications require high spatial resolution. In breast CT, for example, visualization of microcalcifications and assessment of tumor microvasculature after contrast enhancement require resolution on the order of [Formula: see text]. A straightforward approach to increasing spatial resolution of pixellated CZT-based radiation detectors by merely decreasing the pixel size leads to two problems: (1) fabricating circuitry with small pixels becomes costly and (2) inter-pixel charge spreading can obviate any improvement in spatial resolution. We have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve subpixel position resolution. To study these algorithms, we model a simple detector geometry with a [Formula: see text] array of [Formula: see text] pixels, and use a conditional probability function to model charge transport in CZT. We used COMSOL finite element method software to map the distribution of charge pulses and the Monte Carlo package PENELOPE for simulating fluorescent radiation. Performance of two x-ray interaction position estimation algorithms was evaluated: the method of maximum-likelihood estimation and a fast, practical algorithm that can be implemented in a readout application-specific integrated circuit and allows for identification of a quadrant of the pixel in which the interaction occurred. Both methods demonstrate good subpixel resolution; however, their actual efficiency is limited by the presence of fluorescent [Formula: see text]-escape photons. Current experimental breast CT systems typically use
Calderero Patino, Felipe; Marqués Acosta, Fernando; Ortega, Antonio
2009-01-01
Information theoretical region merging techniques have been shown to provide a state-of-the-art unified solution for natural and texture image segmentation. Here, we study how the segmentation results can be further improved by a more accurate estimation of the statistical model characterizing the regions. Concretely, we explore four density estimators that can be used for pdf or joint pdf estimation. The first three are based on different quantization strategies: a general ...
Practical Aspects Of Kernel Smoothing For Binary Regression And Density Estimation
Signorini, David F.
1998-01-01
This thesis explores the practical use of kernel smoothing in three areas: binary regression, density estimation and Poisson regression sample size calculations. Both nonparametric and semiparametric binary regression estimators are examined in detail, and extended to two bandwidth cases. The asymptotic behaviour of these estimators is presented in a unified way, and the practical performance is assessed using a simulation experiment. It is shown that, when using the ideal bandwidth, the ...
International Nuclear Information System (INIS)
Purpose: Estimates of the need for radiotherapy (RT) using different methods (criterion based benchmarking [CBB] and the Canadian [C-EBEST] and Australian [A-EBEST] epidemiologically based estimates) exist for various cancer sites. We compared these model estimates to actual RT rates for lung, breast, and prostate cancers in British Columbia (BC). Methods and Materials: All cases of lung, breast, and prostate cancers in BC from 1997 to 2004 and all patients receiving RT within 1 year (RT1Y) and within 5 years (RT5Y) of diagnosis were identified. The RT1Y and RT5Y proportions in health regions with a cancer center for the most recent year were then calculated. RT rates were compared with CBB and EBEST estimates of RT needs. Variation was assessed by time and region. Results: The RT1Y in regions with a cancer center for lung, breast, and prostate cancers were 51%, 58%, and 33% compared with 45%, 57%, and 32% for C-EBEST and 41%, 61%, and 37% for CBB models. The RT5Y rates in regions with a cancer center for lung, breast, and prostate cancers were 59%, 61%, and 40% compared with 61%, 66%, and 61% for C-EBEST and 75%, 83%, and 60% for A-EBEST models. The RT1Y rates increased for breast and prostate cancers. Conclusions: C-EBEST and CBB model estimates are closer to the actual RT rates than the A-EBEST estimates. Application of these model estimates by health care decision makers should be undertaken with an understanding of the methods used and the assumptions on which they were based.
Rojas-Lima, J. E.; Domínguez-Pacheco, A.; Hernández-Aguilar, C.; Cruz-Orea, A.
2016-09-01
Considering the necessity of photothermal alternative approaches for characterizing nonhomogeneous materials like maize seeds, the objective of this research work was to analyze statistically the amplitude variations of photopyroelectric signals, by means of nonparametric techniques such as the histogram and the kernel density estimator, and the probability density function of the amplitude variations of two genotypes of maize seeds with different pigmentations and structural components: crystalline and floury. To determine if the probability density function had a known parametric form, the histogram was determined which did not present a known parametric form, so the kernel density estimator using the Gaussian kernel, with an efficiency of 95 % in density estimation, was used to obtain the probability density function. The results obtained indicated that maize seeds could be differentiated in terms of the statistical values for floury and crystalline seeds such as the mean (93.11, 159.21), variance (1.64× 103, 1.48× 103), and standard deviation (40.54, 38.47) obtained from the amplitude variations of photopyroelectric signals in the case of the histogram approach. For the case of the kernel density estimator, seeds can be differentiated in terms of kernel bandwidth or smoothing constant h of 9.85 and 6.09 for floury and crystalline seeds, respectively.
Eilertsen, A.L.; Karssemeijer, N.; Skaane, P.; Qvigstad, E.; Sandset, P.M.
2008-01-01
OBJECTIVE: To evaluate impact of different postmenopausal hormone therapy (HT) regimens and raloxifene on mammographic breast density. DESIGN: Open, randomised, comparative clinical trial. SETTING: Women were recruited through local newspapers and posters. They were examined at the Departments of Ha
Sea ice density estimation in the Bohai Sea using the hyperspectral remote sensing technology
Liu, Chengyu; Shao, Honglan; Xie, Feng; Wang, Jianyu
2014-11-01
Sea ice density is one of the significant physical properties of sea ice and the input parameters in the estimation of the engineering mechanical strength and aerodynamic drag coefficients; also it is an important indicator of the ice age. The sea ice in the Bohai Sea is a solid, liquid and gas-phase mixture composed of pure ice, brine pockets and bubbles, the density of which is mainly affected by the amount of brine pockets and bubbles. The more the contained brine pockets, the greater the sea ice density; the more the contained bubbles, the smaller the sea ice density. The reflectance spectrum in 350~2500 nm and density of sea ice of different thickness and ages were measured in the Liaodong Bay of the Bohai Sea during the glacial maximum in the winter of 2012-2013. According to the measured sea ice density and reflectance spectrum, the characteristic bands that can reflect the sea ice density variation were found, and the sea ice density spectrum index (SIDSI) of the sea ice in the Bohai Sea was constructed. The inversion model of sea ice density in the Bohai Sea which refers to the layer from surface to the depth of penetration by the light was proposed at last. The sea ice density in the Bohai Sea was estimated using the proposed model from Hyperion image which is a hyperspectral image. The results show that the error of the sea ice density inversion model is about 0.0004 g•cm-3. The sea ice density can be estimated through hyperspectral remote sensing images, which provide the data support to the related marine science research and application.
Ku, Bon Ki; Evans, Douglas E.
2015-01-01
For nanoparticles with nonspherical morphologies, e.g., open agglomerates or fibrous particles, it is expected that the actual density of agglomerates may be significantly different from the bulk material density. It is further expected that using the material density may upset the relationship between surface area and mass when a method for estimating aerosol surface area from number and mass concentrations (referred to as “Maynard’s estimation method”) is used. Therefore, it is necessary to quantitatively investigate how much the Maynard’s estimation method depends on particle morphology and density. In this study, aerosol surface area estimated from number and mass concentration measurements was evaluated and compared with values from two reference methods: a method proposed by Lall and Friedlander for agglomerates and a mobility based method for compact nonspherical particles using well-defined polydisperse aerosols with known particle densities. Polydisperse silver aerosol particles were generated by an aerosol generation facility. Generated aerosols had a range of morphologies, count median diameters (CMD) between 25 and 50 nm, and geometric standard deviations (GSD) between 1.5 and 1.8. The surface area estimates from number and mass concentration measurements correlated well with the two reference values when gravimetric mass was used. The aerosol surface area estimates from the Maynard’s estimation method were comparable to the reference method for all particle morphologies within the surface area ratios of 3.31 and 0.19 for assumed GSDs 1.5 and 1.8, respectively, when the bulk material density of silver was used. The difference between the Maynard’s estimation method and surface area measured by the reference method for fractal-like agglomerates decreased from 79% to 23% when the measured effective particle density was used, while the difference for nearly spherical particles decreased from 30% to 24%. The results indicate that the use of
Cetacean population density estimation from single fixed sensors using passive acoustics.
Küsel, Elizabeth T; Mellinger, David K; Thomas, Len; Marques, Tiago A; Moretti, David; Ward, Jessica
2011-06-01
Passive acoustic methods are increasingly being used to estimate animal population density. Most density estimation methods are based on estimates of the probability of detecting calls as functions of distance. Typically these are obtained using receivers capable of localizing calls or from studies of tagged animals. However, both approaches are expensive to implement. The approach described here uses a MonteCarlo model to estimate the probability of detecting calls from single sensors. The passive sonar equation is used to predict signal-to-noise ratios (SNRs) of received clicks, which are then combined with a detector characterization that predicts probability of detection as a function of SNR. Input distributions for source level, beam pattern, and whale depth are obtained from the literature. Acoustic propagation modeling is used to estimate transmission loss. Other inputs for density estimation are call rate, obtained from the literature, and false positive rate, obtained from manual analysis of a data sample. The method is applied to estimate density of Blainville's beaked whales over a 6-day period around a single hydrophone located in the Tongue of the Ocean, Bahamas. Results are consistent with those from previous analyses, which use additional tag data. PMID:21682386
International Nuclear Information System (INIS)
Aim: To assess whether the size of peritumoural stiffness (PTS) on shear-wave elastography (SWE) for small primary breast cancers (≤15 mm) was associated with size discrepancies between grey-scale ultrasound (GSUS) and final histological size and whether the addition of PTS size to GSUS size might result in more accurate tumour size estimation when compared to final histological size. Materials and methods: A retrospective analysis of 86 consecutive patients between August 2011 and February 2013 who underwent breast-conserving surgery for tumours of size ≤15 mm at ultrasound was carried out. The size of PTS stiffness was compared to mean GSUS size, mean histological size, and the extent of size discrepancy between GSUS and histology. PTS size and GSUS were combined and compared to the final histological size. Results: PTS of >3 mm was associated with a larger mean final histological size (16 versus 11.3 mm, p < 0.001). PTS size of >3 mm was associated with a higher frequency of underestimation of final histological size by GSUS of >5 mm (63% versus 18%, p < 0.001). The combination of PTS and GSUS size led to accurate estimation of the final histological size (p = 0.03). The size of PTS was not associated with margin involvement (p = 0.27). Conclusion: PTS extending beyond 3 mm from the grey-scale abnormality is significantly associated with underestimation of tumour size of >5 mm for small invasive breast cancers. Taking into account the size of PTS also led to accurate estimation of the final histological size. Further studies are required to assess the relationship of the extent of SWE stiffness and margin status. - Highlights: • Peritumoural stiffness of greater than 3 mm was associated with larger tumour size. • Underestimation of tumour size by ultrasound was associated with peri-tumoural stiffness size. • Combining peri-tumoural stiffness size to ultrasound produced accurate tumour size estimation
DEFF Research Database (Denmark)
Pettersen, P.C.; Raundahl, Jakob; Loog, M.; Nielsen, Mads; Tankó, L.B.; Christiansen, C.
2008-01-01
trial, active treatment induced a significant increase in breast density, which was consistent in all methods used (all p < 0.05). In contrast, none of the methods detected significant changes in women receiving nasal HRT. The sensitivity of automated methods to discriminate HRT- from placebo...... of changes in breast density induced by hormones and could serve as a useful tool in future clinical trials....
van Uytven, Eric Peter
Screening mammography is the current standard in detecting breast cancer. However, its fundamental disadvantage is that it projects a 3D object into a 2D image. Small lesions are difficult to detect when superimposed over layers of normal tissue. Commercial Computed Tomography (CT) produces a true 3D image yet has a limited role in mammography due to relatively low resolution and contrast. With the intent of enhancing mammography and breast CT, we have developed an algorithm which can produce 3D electron density images using a single projection. Imaging an object with x rays produces a characteristic scattered photon spectrum at the detector plane. A known incident beam spectrum, beam shape, and arbitrary 3D matrix of electron density values enable a theoretical scattered photon distribution to be calculated. An iterative minimization algorithm is used to make changes to the electron density voxel matrix to reduce regular differences between the theoretical and the experimentally measured distributions. The object is characterized by the converged electron density image. This technique has been validated in simulation using data produced by the EGSnrc Monte Carlo code system. At both mammographic and CT energies, a scanning polychromatic pencil beam was used to image breast tissue phantoms containing lesion-like inhomogeneities. The resulting Monte Carlo data is processed using a Nelder-Mead iterative algorithm (MATLAB) to produce the 3D matrix of electron density values. Resulting images have confirmed the ability of the algorithm to detect various 1x1x2.5 mm3 lesions with calcification content as low as 0.5% (p<0.005) at a dose comparable to mammography.
Estimating population density and connectivity of American mink using spatial capture-recapture.
Fuller, Angela K; Sutherland, Chris S; Royle, J Andrew; Hare, Matthew P
2016-06-01
Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture-recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture-recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km² area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture-recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species. PMID:27509753
International Nuclear Information System (INIS)
Ultrasound is not an efficacious screening modality to detect early-stage breast malignancy in a clinically unremarkable population of women. Computed body tomography is similarly not practical for screening because of slice thickness and partial volume averaging, a higher radiation dose than modern mammography, and the lack of availability of such units for such a high throughput requirement. Nevertheless, these two imaging modalities can be very useful in management to guide the least invasive and efficacious treatment of the patient. X-ray mammography remains the principal imaging modality in the search for breast malignancy, but ultrasound is the single most important second study in the diagnostic evaluation of the breast. The combined use of these techniques and the ability to perform guided aspiration and localization procedures can result in a reduction in the surgical removal of benign cysts and reduction in the amount of tissue volume required if excision becomes necessary
Alterations of monocarboxylate transporter densities during hypoxia in brain and breast tumour cells
DEFF Research Database (Denmark)
Cheng, Chang; Edin, Nina F Jeppesen; Lauritzen, Knut H;
2012-01-01
Tumour cells are characterized by aerobic glycolysis, which provides biomass for tumour proliferation and leads to extracellular acidification through efflux of lactate via monocarboxylate transporters (MCTs). Deficient and spasm-prone tumour vasculature causes variable hypoxia, which favours tum...... tumour cell survival and metastases. Brain metastases frequently occur in patients with advanced breast cancer.Effective treatment strategies are therefore needed against brain metastasis from breast carcinoma....
Directory of Open Access Journals (Sweden)
Yousri Slaoui
2014-01-01
Full Text Available We propose an automatic selection of the bandwidth of the recursive kernel estimators of a probability density function defined by the stochastic approximation algorithm introduced by Mokkadem et al. (2009a. We showed that, using the selected bandwidth and the stepsize which minimize the MISE (mean integrated squared error of the class of the recursive estimators defined in Mokkadem et al. (2009a, the recursive estimator will be better than the nonrecursive one for small sample setting in terms of estimation error and computational costs. We corroborated these theoretical results through simulation study.
Directory of Open Access Journals (Sweden)
Aggarwal Himanshu
2007-01-01
Full Text Available The change in expression of apoptotic markers (Bcl-2 and Bax proteins brought about by various chemotherapeutic regimens is being used for its predictive value for assessing response to neoadjuvant chemotherapy (NACT in locally advanced breast carcinoma (LABC. Aims: (1 Estimation of Bcl 2 expression in LABC, (2 Any change in Bcl 2 expression following chemotherapy in LABC, (3 Any relation of Bcl 2 estimation to changes in size of tumor, nodal status, age, and menopausal status. Settings and Design: This was a prospective study of 120 cases of LABC. Materials and Methods: All cases were subjected to biopsy and the tissue was evaluated immunohistochemically for apoptotic marker Bcl-2 family protein. Three cycles of NACT were given at three-weekly intervals. Modified radical mastectomy was performed and the specimens were re-evaluated for any change in the Bcl-2 family protein. The clinical response and immunohistochemical response were correlated and compared. Statistical Analysis: Coefficient of correlation was calculated by Pearson correlation coefficient (P-value. Results: Clinical response, as measured by reduction in the tumor size, was observed in 81 (67.5% patients while immunohistochemical response was observed in 67 (55.8% patients. Correlation between immunohistochemical and clinical response was found to be statistically significant (P = 0.02. Nodal response was seen in 72 (60% patients. There were no patients in the N o group; 22 (53.7% of the N 1 patients were down-staged to N o , while 19 (46.3% remained N 1 . In patients with N 2 disease, 11 (13.9% were down-staged to N o status, 39 (49.4% were down-staged to N 1 status, and 29 (36.7% did not show any response. Immunohistochemical response was observed in 67 (55.8% patients. Correlation between immunohistochemical and nodal responses was also found to be statistically significant (P = 0.03. Conclusions: This significant positive correlation between clinical and immunohistochemical
Energy Technology Data Exchange (ETDEWEB)
Koo, Hye Ryoung, E-mail: huilings@hanmail.net [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Moon, Woo Kyung, E-mail: moonwk@snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Chun, In Kook, E-mail: inkook.chun@gmail.com [Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Eo, Jae Seon, E-mail: jaeseon76@gmail.com [Department of Nuclear Medicine, Korea University Guro Hospital, 148 Gurodongro, Guro-gu, Seoul 152-703 (Korea, Republic of); Jeyanth, Joseph Xavier, E-mail: jeyanth7@snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Chang, Jung Min, E-mail: imchangjm@gmail.com [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Cho, Nariya, E-mail: river7774@gmail.com [Department of Radiology, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of); Kang, Keon Wook, E-mail: kangkw@snu.ac.kr [Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744 (Korea, Republic of)
2013-10-01
We aimed to determine whether background {sup 18}F-FDG uptake in positron emission mammography (PEM) was related to mammographic density or background parenchymal enhancement in breast MRI. Methods: We studied a total of 52 patients (mean age, 50.9 years, 26 premenopausal, 26 postmenopausal) with newly diagnosed breast cancer who underwent {sup 18}F-FDG PEM (positron emission mammography), conventional mammography and breast MRI. The background mean {sup 18}F-FDG uptake value on PEM was obtained by drawing a user-defined region of interest (ROI) in a normal area of the contralateral breast. We reviewed the mammography retrospectively for overall breast density of contralateral breast according to the four-point scale (grade 1–4) of the Breast Imaging Reporting and Data System (BI-RADS) classification. The background parenchymal enhancement of breast MRI was classified as minimal, mild, moderate, or marked. All imaging findings were interpreted by two readers in consensus without knowledge of image findings of other modalities. Results: Multiple linear regression analysis revealed a significant correlation between background {sup 18}F-FDG uptake on PEM and mammographic density after adjustment for age and menopausal status (P < 0.01), but not between background {sup 18}F-FDG uptake on PEM and background parenchymal enhancement on MRI. Conclusion: Background {sup 18}F-FDG uptake on PEM significantly increases as mammographic density increases. Background parenchymal enhancement in breast MRI was not an independent predictor of the background {sup 18}F-FDG uptake on PEM unlike mammographic density.
A Greedy Algorithm for Unimodal Kernel Density Estimation by Data Sharpening
Directory of Open Access Journals (Sweden)
Mark A. Wolters
2012-04-01
Full Text Available We consider the problem of nonparametric density estimation where estimates are constrained to be unimodal. Though several methods have been proposed to achieve this end, each of them has its own drawbacks and none of them have readily-available computer codes. The approach of Braun and Hall (2001, where a kernel density estimatoris modified by data sharpening, is one of the most promising options, but optimization difficulties make it hard to use in practice. This paper presents a new algorithm and MATLAB code for finding good unimodal density estimates under the Braun and Hall scheme. The algorithm uses a greedy, feasibility-preserving strategy to ensure that it always returns a unimodal solution. Compared to the incumbent method of optimization, the greedy method is easier to use, runs faster, and produces solutions of comparable quality. It can also be extended to the bivariate case.
LSTA, Rawane Samb
2010-01-01
This thesis deals with the nonparametric estimation of density f of the regression error term E of the model Y=m(X)+E, assuming its independence with the covariate X. The difficulty linked to this study is the fact that the regression error E is not observed. In a such setup, it would be unwise, for estimating f, to use a conditional approach based upon the probability distribution function of Y given X. Indeed, this approach is affected by the curse of dimensionality, so that the resulting estimator of the residual term E would have considerably a slow rate of convergence if the dimension of X is very high. Two approaches are proposed in this thesis to avoid the curse of dimensionality. The first approach uses the estimated residuals, while the second integrates a nonparametric conditional density estimator of Y given X. If proceeding so can circumvent the curse of dimensionality, a challenging issue is to evaluate the impact of the estimated residuals on the final estimator of the density f. We will also at...
An automatic iris occlusion estimation method based on high-dimensional density estimation.
Li, Yung-Hui; Savvides, Marios
2013-04-01
Iris masks play an important role in iris recognition. They indicate which part of the iris texture map is useful and which part is occluded or contaminated by noisy image artifacts such as eyelashes, eyelids, eyeglasses frames, and specular reflections. The accuracy of the iris mask is extremely important. The performance of the iris recognition system will decrease dramatically when the iris mask is inaccurate, even when the best recognition algorithm is used. Traditionally, people used the rule-based algorithms to estimate iris masks from iris images. However, the accuracy of the iris masks generated this way is questionable. In this work, we propose to use Figueiredo and Jain's Gaussian Mixture Models (FJ-GMMs) to model the underlying probabilistic distributions of both valid and invalid regions on iris images. We also explored possible features and found that Gabor Filter Bank (GFB) provides the most discriminative information for our goal. Finally, we applied Simulated Annealing (SA) technique to optimize the parameters of GFB in order to achieve the best recognition rate. Experimental results show that the masks generated by the proposed algorithm increase the iris recognition rate on both ICE2 and UBIRIS dataset, verifying the effectiveness and importance of our proposed method for iris occlusion estimation. PMID:22868651
[Estimation of Hunan forest carbon density based on spectral mixture analysis of MODIS data].
Yan, En-ping; Lin, Hui; Wang, Guang-xing; Chen, Zhen-xiong
2015-11-01
With the fast development of remote sensing technology, combining forest inventory sample plot data and remotely sensed images has become a widely used method to map forest carbon density. However, the existence of mixed pixels often impedes the improvement of forest carbon density mapping, especially when low spatial resolution images such as MODIS are used. In this study, MODIS images and national forest inventory sample plot data were used to conduct the study of estimation for forest carbon density. Linear spectral mixture analysis with and without constraint, and nonlinear spectral mixture analysis were compared to derive the fractions of different land use and land cover (LULC) types. Then sequential Gaussian co-simulation algorithm with and without the fraction images from spectral mixture analyses were employed to estimate forest carbon density of Hunan Province. Results showed that 1) Linear spectral mixture analysis with constraint, leading to a mean RMSE of 0.002, more accurately estimated the fractions of LULC types than linear spectral and nonlinear spectral mixture analyses; 2) Integrating spectral mixture analysis model and sequential Gaussian co-simulation algorithm increased the estimation accuracy of forest carbon density to 81.5% from 74.1%, and decreased the RMSE to 5.18 from 7.26; and 3) The mean value of forest carbon density for the province was 30.06 t · hm(-2), ranging from 0.00 to 67.35 t · hm(-2). This implied that the spectral mixture analysis provided a great potential to increase the estimation accuracy of forest carbon density on regional and global level. PMID:26915200
PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA
Henrique Seixas Barros; Philip Martin Fearnside
2015-01-01
Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk d...
Ozkurt, Celil; Camci, Fatih
2009-01-01
It is important to know the road traffic density real time especially in mega cities for signal control and effective traffic management. In recent years, video monitoring and surveillance systems have been widely used in traffic management. Hence, traffic density estimation and vehicle classification can be achieved using video monitoring systems. In most vehicle detection methods in the literature, only the detection of vehicles in frames of the given video is emphesized. However, further a...
Santos, André Duarte dos
2011-01-01
This thesis examines the stability and accuracy of three different methods to estimate Risk-Neutral Density functions (RNDs) using European options. These methods are the Double-Lognormal Function (DLN), the Smoothed Implied Volatility Smile (SML) and the Density Functional Based on Confluent Hypergeometric function (DFCH). These methodologies were used to obtain the RNDs from the option prices with the underlying USDBRL (price of US dollars in terms of Brazilian reals) for different maturiti...
Susaki, J.
2016-06-01
In this paper, we analyze probability density functions (PDFs) of scatterings derived from fully polarimetric synthetic aperture radar (SAR) images for improving the accuracies of estimated urban density. We have reported a method for estimating urban density that uses an index Tv+c obtained by normalizing the sum of volume and helix scatterings Pv+c. Validation results showed that estimated urban densities have a high correlation with building-to-land ratios (Kajimoto and Susaki, 2013b; Susaki et al., 2014). While the method is found to be effective for estimating urban density, it is not clear why Tv+c is more effective than indices derived from other scatterings, such as surface or double-bounce scatterings, observed in urban areas. In this research, we focus on PDFs of scatterings derived from fully polarimetric SAR images in terms of scattering normalization. First, we introduce a theoretical PDF that assumes that image pixels have scatterers showing random backscattering. We then generate PDFs of scatterings derived from observations of concrete blocks with different orientation angles, and from a satellite-based fully polarimetric SAR image. The analysis of the PDFs and the derived statistics reveals that the curves of the PDFs of Pv+c are the most similar to the normal distribution among all the scatterings derived from fully polarimetric SAR images. It was found that Tv+c works most effectively because of its similarity to the normal distribution.
Limit distribution theory for maximum likelihood estimation of a log-concave density
Balabdaoui, Fadoua; Rufibach, Kaspar; Wellner, Jon
2009-01-01
We find limiting distributions of the nonparametric maximum likelihood estimator (MLE) of a log-concave density, i.e. a density of the form f0 = exp ϕ0 where ϕ0 is a concave function on ℝ. Existence, form, characterizations and uniform rates of convergence of the MLE are given by Rufibach (2006) and Dümbgen and Rufibach (2007). The characterization of the log–concave MLE in terms of distribution functions is the same (up to sign) as the characterization of the least squares estimator of a con...
PEDO-TRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY IN CENTRAL AMAZONIA
Directory of Open Access Journals (Sweden)
Henrique Seixas Barros
2015-04-01
Full Text Available Under field conditions in the Amazon forest, soil bulk density is difficult to measure. Rigorous methodological criteria must be applied to obtain reliable inventories of C stocks and soil nutrients, making this process expensive and sometimes unfeasible. This study aimed to generate models to estimate soil bulk density based on parameters that can be easily and reliably measured in the field and that are available in many soil-related inventories. Stepwise regression models to predict bulk density were developed using data on soil C content, clay content and pH in water from 140 permanent plots in terra firme (upland forests near Manaus, Amazonas State, Brazil. The model results were interpreted according to the coefficient of determination (R2 and Akaike information criterion (AIC and were validated with a dataset consisting of 125 plots different from those used to generate the models. The model with best performance in estimating soil bulk density under the conditions of this study included clay content and pH in water as independent variables and had R2 = 0.73 and AIC = -250.29. The performance of this model for predicting soil density was compared with that of models from the literature. The results showed that the locally calibrated equation was the most accurate for estimating soil bulk density for upland forests in the Manaus region.
Directory of Open Access Journals (Sweden)
Eléanor Brassine
Full Text Available Camera trapping studies have become increasingly popular to produce population estimates of individually recognisable mammals. Yet, monitoring techniques for rare species which occur at extremely low densities are lacking. Additionally, species which have unpredictable movements may make obtaining reliable population estimates challenging due to low detectability. Our study explores the effectiveness of intensive camera trapping for estimating cheetah (Acinonyx jubatus numbers. Using both a more traditional, systematic grid approach and pre-determined, targeted sites for camera placement, the cheetah population of the Northern Tuli Game Reserve, Botswana was sampled between December 2012 and October 2013. Placement of cameras in a regular grid pattern yielded very few (n = 9 cheetah images and these were insufficient to estimate cheetah density. However, pre-selected cheetah scent-marking posts provided 53 images of seven adult cheetahs (0.61 ± 0.18 cheetahs/100 km². While increasing the length of the camera trapping survey from 90 to 130 days increased the total number of cheetah images obtained (from 53 to 200, no new individuals were recorded and the estimated population density remained stable. Thus, our study demonstrates that targeted camera placement (irrespective of survey duration is necessary for reliably assessing cheetah densities where populations are naturally very low or dominated by transient individuals. Significantly our approach can easily be applied to other rare predator species.
Directory of Open Access Journals (Sweden)
Carlos B. Kasper
2015-09-01
Full Text Available ABSTRACT Using camera traps and capture/recapture analyses we recorded the presence and abundance of cat species at Turvo State Park, in southern Brazil. Ocelot [Leopardus pardalis (Linnaeus, 1758] population density was estimated for two areas of the park, with differing management profiles. Density estimates varied from 0.14 to 0.26 indiv. km2. Another five cat species were recorded at very low frequencies, precluding more accurate analyses. We estimate 24 to 45 ocelots occur in the reserve, which is probably too small for long-term maintenance of the population, if isolated. However, if habitat integrity and connectivity between the Park and the Green Corridor of Misiones is maintained, an estimated ocelot population of 1,680 individuals should have long-term viability.
Scent Lure Effect on Camera-Trap Based Leopard Density Estimates.
Directory of Open Access Journals (Sweden)
Alexander Richard Braczkowski
Full Text Available Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a 'control' and 'treatment' survey on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96 or temporal activity of female (p = 0.12 or male leopards (p = 0.79, and the assumption of geographic closure was met for both surveys (p >0.05. The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90. Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28-9.28 leopards/100km2 were considerably higher than estimates from spatially-explicit methods (3.40-3.65 leopards/100km2. The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.
The importance of spatial models for estimating the strength of density dependence
DEFF Research Database (Denmark)
Thorson, James T.; Skaug, Hans J.; Kristensen, Kasper;
2014-01-01
the California Coast. In this case, the nonspatial model estimates implausible oscillatory dynamics on an annual time scale, while the spatial model estimates strong autocorrelation and is supported by model selection tools. We conclude by discussing the importance of improved data archiving techniques, so...... that spatial models can be used to re-examine classic questions regarding the presence and strength of density dependence in wild populations Read More: http://www.esajournals.org/doi/abs/10.1890/14-0739.1...
Nara, Takaaki; Koike, Masanori; Ando, Shigeru; Gotoh, Yuji; Izumi, Masaaki
2016-05-01
In this paper, we propose novel inversion methods to estimate defects or localized current anomalies in membrane electrode assemblies (MEAs) in polymer electrolyte fuel cells (PEFCs). One method is an imaging approach with L1-norm regularization that is suitable for estimation of focal anomalies compared to Tikhonov regularization. The second is a complex analysis based method in which multiple pointwise current anomalies can be identified directly and algebraically from the measured magnetic flux density.
Variational estimation of the drift for stochastic differential equations from the empirical density
Batz, Philipp; Opper, Manfred
2016-01-01
We present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation of the Fokker-Planck equation. The minimization of an empirical estimate of the variational functional using kernel based regularization can be performed in closed form. We demonstrate the performance of the method on second order, Langevin-type equations and show how the method can be generalized to other noise models.
Non-Parametric Bayesian Measurement Noise Density Estimation in Non-Linear Filtering
Czech Academy of Sciences Publication Activity Database
Okzan, E.; Saha, S.; Gustafsson, F.; Šmídl, Václav
Piscataway : IEEE, 2011, s. 5924-5927. ISBN 978-1-4577-0539-7. [IEEE International Conference on Acoustics , Speech and Signal Processing. Praha (CZ), 22.05.2011-27.05.2011] Institutional research plan: CEZ:AV0Z10750506 Keywords : Particle filtering * Dirichlet process * Bayesian Estimation Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2011/AS/smidl-non-parametric bayesian measurement noise density estimation in non-linear filtering.pdf
Estimation of current density distribution of PAFC by analysis of cell exhaust gas
Energy Technology Data Exchange (ETDEWEB)
Kato, S.; Seya, A. [Fuji Electric Co., Ltd., Ichihara-shi (Japan); Asano, A. [Fuji Electric Corporate, Ltd., Yokosuka-shi (Japan)
1996-12-31
To estimate distributions of Current densities, voltages, gas concentrations, etc., in phosphoric acid fuel cell (PAFC) stacks, is very important for getting fuel cells with higher quality. In this work, we leave developed a numerical simulation tool to map out the distribution in a PAFC stack. And especially to Study Current density distribution in the reaction area of the cell, we analyzed gas composition in several positions inside a gas outlet manifold of the PAFC stack. Comparing these measured data with calculated data, the current density distribution in a cell plane calculated by the simulation, was certified.
Identification of the monitoring point density needed to reliably estimate contaminant mass fluxes
Liedl, R.; Liu, S.; Fraser, M.; Barker, J.
2005-12-01
Plume monitoring frequently relies on the evaluation of point-scale measurements of concentration at observation wells which are located at control planes or `fences' perpendicular to groundwater flow. Depth-specific concentration values are used to estimate the total mass flux of individual contaminants through the fence. Results of this approach, which is based on spatial interpolation, obviously depend on the density of the measurement points. Our contribution relates the accurracy of mass flux estimation to the point density and, in particular, allows to identify a minimum point density needed to achieve a specified accurracy. In order to establish this relationship, concentration data from fences installed in the coal tar creosote plume at the Borden site are used. These fences are characterized by a rather high density of about 7 points/m2 and it is reasonable to assume that the true mass flux is obtained with this point density. This mass flux is then compared with results for less dense grids down to about 0.1points/m2. Mass flux estimates obtained for this range of point densities are analyzed by the moving window method in order to reduce purely random fluctuations. For each position of the moving window the mass flux is estimated and the coefficient of variation (CV) is calculated to quantify variablity of the results. Thus, the CV provides a relative measure of accurracy in the estimated fluxes. By applying this approach to the Borden naphthalene plume at different times, it is found that the point density changes from sufficient to insufficient due to the temporally decreasing mass flux. By comparing the results of naphthalene and phenol at the same fence and at the same time, we can see that the same grid density might be sufficient for one compound but not for another. If a rather strict CV criterion of 5% is used, a grid of 7 points/m2 is shown to allow for reliable estimates of the true mass fluxes only in the beginning of plume development when
International Nuclear Information System (INIS)
The purpose of this study was to measure the peripheral dose which is the absorbed dose in organs located outside the treatment volume such as the thyroid gland and the breast in patients undergoing radiotherapy, utilising the MOSFET dosemeters, as well as to estimate the probability of secondary cancer. The thyroid gland doses, expressed as a percentage of the prescribed dose (%TD), were measured to be 2.0±0.3 %, in whole brain irradiation, 10.0±8.0 % in mediastinum treatment and 8.0±2.0 and 2.0±0.8 % in breast treatment, with and without the supraclavicular irradiation, respectively, with a corresponding risk of 0.2, 2.0, 1.0 and 0.3 %. The dose to the breast was 7.0±2.0 %, in the mediastinum treatment, and 4.0±1.0 and 2.0±0.8 %, in the breast treatment, with and without supraclavicular irradiation, respectively, with a corresponding risk of 4.0, 2.0 and 1.0 %. Although the results indicate that the risk is not negligible, its significance should be considered in conjunction with the existing pathology and age of the patients. (authors)
Institute of Scientific and Technical Information of China (English)
Farah Yasmeen[1; Sidra Zaheer[2
2014-01-01
Background： Breast cancer is the most common female cancer in Pakistan. The incidence of breast cancer in Pakistan is about 2.5 times higher than that in the neighboring countries India and Iran. In Karachi, the most populated city of Pakistan, the age-standardized rate of breast cancer was 69.1 per 100,000 women during 1998-2002, which is the highest recorded rate in Asia. The carcinoma of breast in Pakistan is an enormous public health concern. In this study, we examined the recent trends of breast cancer incidence rates among the women in Karachi. Methods： We obtained the secondary data of breast cancer incidence from various hospitals. They included Jinnah Hospital, KIRAN （Karachi Institute of Radiotherapy and Nuclear Medicine）, and Civil hospital, where the data were available for the years 2004-2011. A total of 5331 new cases of female breast cancer were registered during this period. We analyzed the data in 5-year age groups 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75＋. Nonparametric smoothing were used to obtained age-specific incidence curves, and then the curves are decomposed using principal components analysis to fit FTS （functional time series） model. We then used exponential smoothing statspace models to estimate the forecasts of incidence curve and construct prediction intervals. Results： The breast cancer incidence rates in Karachi increased with age for all available years. The rates increased monotonically and are relatively sharp with the age from 15 years to 50 years and then they show variability after the age of 50 years. 10-year forecasts for the female breast cancer incidence rates in Karachi show that the future rates are expected to remain stable for the age-groups 15-50 years, but they will increase for the females of 50-years and over. Hence in future, the newly diagnosed breast cancer cases in the older women in Karachi are expected to increase. Conclusion： Prediction of age
Estimation of the global 222Rn flux density from the earth's surface
International Nuclear Information System (INIS)
Global 222Rn flux density distributions with a spatial resolution of 1deg in latitude and longitude were estimated for each month in the period of 1979-2007 using an 222Rn exhalation model based on a porous media diffusion theory. This exhalation model calculated the 222Rn flux density as a function of the 226Ra content, soil water saturation, and soil temperature. The influence of the topographical ruggedness of the ground surface on the flux density was also considered in the model. The global average of the flux density during the 29-year period was estimated to be 21.3 mBq m-2 s-1. The annual variation in the globally averaged flux density showed a slight but steady increase since 1999. The seasonal variation in the globally averaged flux density was estimated to range from a minimum of 18.8 mBq m-2 s-1 in March to a maximum of 23.6 mBq m-2 s-1 in September. The regional averages for the annual flux density varied from 8.3 mBq m-2 s-1 for the northern part of North America to 33.5 mBq m-2 s-1 for Australia. The latitudinal distribution of zonally averaged flux density was found to be in good agreement with the latitudinal decline at high latitudes in the Northern Hemisphere. The spatial and temporal variations were caused mainly by variations in the soil water content and soil 226Ra content, but to a lesser extent by the soil temperature. The topographical ruggedness was found to increase the flux density by only 2% globally but by more than 10% in mountainous regions. Atmospheric transport simulation using the estimated flux density as input data showed that the simulated atmospheric 222Rn concentration was substantially lower than that measured at Hachijo Island, implying that the flux density of the present study with topographical ruggedness is still underestimated in the East Asian region. (author)
Change-Point Detection in Time-Series Data by Relative Density-Ratio Estimation
Liu, Song; Collier, Nigel; Sugiyama, Masashi
2012-01-01
The objective of change-point detection is to discover abrupt property changes lying behind time series data. In this paper, we present a novel statistical change-point detection algorithm that is based on non-parametric divergence estimation between two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and efficiently estimated by a method of direct density-ratio estimation. Through experiments on artificial and real-world datasets including human-activity sensing, speeches, and Twitter archives, we demonstrate the usefulness of the proposed method.
Kim, Sunmi; Lee, Jangwoo; Park, Jeongim; Kim, Hai-Joong; Cho, Geumjoon; Kim, Gun-Ha; Eun, So-Hee; Lee, Jeong Jae; Choi, Gyuyeon; Suh, Eunsook; Choi, Sooran; Kim, Sungjoo; Kim, Young Don; Kim, Sung Koo; Kim, Su Young; Kim, Seunghyo; Eom, Soyong; Moon, Hyo-Bang; Kim, Sungkyoon; Choi, Kyungho
2015-03-01
Phthalates have been associated with endocrine disruption and developmental effects in many experimental and epidemiological studies. Developing infants are among the most susceptible populations to endocrine disruption. However, limited information is available on phthalate exposure and its associated risks among breast-fed newborn infants. In the present study, breast milk samples were collected from 62 lactating mothers at 1 month post-partum from four cities of Korea in 2012 and were evaluated for six phthalate metabolites (mono-isobutyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), mono(2-ethyl-hexyl) phthalate (MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) and monoethyl phthalate (MEP)). MEP was detected in all breast milk samples, with a median concentration of 0.37 μg/L, and MiBP, MnBP and MEHP were detected in 79-89% of samples, with median concentrations of 1.10, 1.70, and 2.08 μg/L, respectively. However, MEHHP and MEOHP, the oxidized forms of di-ethyl-hexyl phthalate (DEHP), were detected in only one sample. For exposure assessment, the levels of phthalate diesters were estimated based on the parent:metabolite ratios in the breast milk that are reported elsewhere. For risk assessment, the endocrine-related toxicity of the monoester was assumed to be the same as that of its diester form. Median daily intake estimates of phthalates, including both monoester and diester forms, through breast milk consumption ranged between 0.91 and 6.52 μg/kg body weight (bw) for DEHP and between 0.38 and 1.43 μg/kg bw for di-n-butyl phthalate (DnBP). Based on the estimated daily intake, up to 8% of infants exceeded the reference dose of anti-androgenicity (RfD AA) for DEHP, and 6% of infants exceeded the tolerable daily intake (TDI) for DnBP. Breast milk MiBP and MnBP concentrations showed significant positive associations with maternal consumption of whipped cream or purified water. Considering vulnerability of
Compound kernel estimates for the transition probability density of a L\\'evy process in $\\rn$
Knopova, V.
2013-01-01
We construct in the small-time setting the upper and lower estimates for the transition probability density of a L\\'evy process in $\\rn$. Our approach relies on the complex analysis technique and the asymptotic analysis of the inverse Fourier transform of the characteristic function of the respective process.
Eurasian otter (Lutra lutra) density estimate based on radio tracking and other data sources
Czech Academy of Sciences Publication Activity Database
Quaglietta, L.; Hájková, Petra; Mira, A.; Boitani, L.
2015-01-01
Roč. 60, č. 2 (2015), s. 127-137. ISSN 2199-2401 R&D Projects: GA AV ČR KJB600930804 Institutional support: RVO:68081766 Keywords : Lutra lutra * Density estimation * Edge effect * Known-to-be-alive * Linear habitats * Sampling scale Subject RIV: EG - Zoology
Estimation of nighttime dip-equatorial E-region current density using measurements and models
Pandey, Kuldeep; Sekar, R.; Anandarao, B. G.; Gupta, S. P.; Chakrabarty, D.
2016-08-01
The existence of the possible ionospheric current during nighttime over low-equatorial latitudes is one of the unresolved issues in ionospheric physics and geomagnetism. A detailed investigation is carried out to estimate the same over Indian longitudes using in situ measurements from Thumba (8.5 ° N, 76.9 ° E), empirical plasma drift model (Fejer et al., 2008) and equatorial electrojet model developed by Anandarao (1976). This investigation reveals that the nighttime E-region current densities vary from ∼0.3 to ∼0.7 A/km2 during pre-midnight to early morning hours on geomagnetically quiet conditions. The nighttime current densities over the dip equator are estimated using three different methods (discussed in methodology section) and are found to be consistent with one another within the uncertainty limits. Altitude structures in the E-region current densities are also noticed which are shown to be associated with altitudinal structures in the electron densities. The horizontal component of the magnetic field induced by these nighttime ionospheric currents is estimated to vary between ∼2 and ∼6 nT during geomagnetically quiet periods. This investigation confirms the existence of nighttime ionospheric current and opens up a possibility of estimating base line value for geomagnetic field fluctuations as observed by ground-based magnetometer.
Estimating and Testing Continuous-Time Models in Finance: The Role of Transition Densities
Yacine Aït-Sahalia
2009-01-01
This article surveys recent developments to estimate and test continuous-time models in finance using discrete observations on the underlying asset price or derivative securities' prices. Both parametric and nonparametric methods are described. All these methods share a common focus on the transition density as the central object for inference and testing of the model.
MODERATE DEVIATIONS AND LARGE DEVIATIONS FOR A TEST OF SYMMETRY BASED ON KERNEL DENSITY ESTIMATOR
Institute of Scientific and Technical Information of China (English)
He Xiaoxia; Gao Fuqing
2008-01-01
Let fn be a non-parametric kernel density estimator based on a kernel function K. And a sequence of independent and identically distributed random variables taking values in R. The goal of this article is to prove moderate deviations and large deviations for the statistic sup x∈R|fn(x) - fn(-X)|.
International Nuclear Information System (INIS)
The UK and European protocols for mammographic dosimetry use conversion factors that relate incident air kerma to the mean glandular dose (MGD) within the breast. The conversion factors currently used were obtained by computer simulation of a model breast with a composition of 50% adipose and 50% glandular tissues by weight (50% glandularity). Relative conversion factors have been calculated which allow the extension of the protocols to breasts of varying glandularity and for a wider range of mammographic x-ray spectra. The data have also been extended to breasts of a compressed thickness of 11 cm. To facilitate the calculation of MGD in patient surveys, typical breast glandularities are tabulated for women in the age ranges 40-49 and 50-64 years, and for breasts in the thickness range 2-11 cm. In addition, tables of equivalent thickness of polymethyl methacrylate have been provided to allow the simulation for dosimetric purposes of typical breasts of various thicknesses. (author)
Estimation of high-resolution dust column density maps: Empirical model fits
Juvela, M
2013-01-01
Sub-millimetre dust emission is an important tracer of density N of dense interstellar clouds. One has to combine surface brightness information at different spatial resolutions, and specific methods are needed to derive N at a resolution higher than the lowest resolution of the observations. Some methods have been discussed in the literature, including a method (in the following, method B) that constructs the N estimate in stages, where the smallest spatial scales being derived only use the shortest wavelength maps. We propose simple model fitting as a flexible way to estimate high-resolution column density maps. Our goal is to evaluate the accuracy of this procedure and to determine whether it is a viable alternative for making these maps. The new method consists of model maps of column density (or intensity at a reference wavelength) and colour temperature. The model is fitted using Markov chain Monte Carlo (MCMC) methods, comparing model predictions with observations at their native resolution. We analyse...
Robel, G.L.; Fisher, W.L.
1999-01-01
Production of and consumption by hatchery-reared tingerling (age-0) smallmouth bass Micropterus dolomieu at various simulated stocking densities were estimated with a bioenergetics model. Fish growth rates and pond water temperatures during the 1996 growing season at two hatcheries in Oklahoma were used in the model. Fish growth and simulated consumption and production differed greatly between the two hatcheries, probably because of differences in pond fertilization and mortality rates. Our results suggest that appropriate stocking density depends largely on prey availability as affected by pond fertilization and on fingerling mortality rates. The bioenergetics model provided a useful tool for estimating production at various stocking density rates. However, verification of physiological parameters for age-0 fish of hatchery-reared species is needed.
Codis, Sandrine; Bernardeau, Francis; Pichon, Christophe
2016-08-01
In order to quantify the error budget in the measured probability distribution functions of cell densities, the two-point statistics of cosmic densities in concentric spheres is investigated. Bias functions are introduced as the ratio of their two-point correlation function to the two-point correlation of the underlying dark matter distribution. They describe how cell densities are spatially correlated. They are computed here via the so-called large deviation principle in the quasi-linear regime. Their large-separation limit is presented and successfully compared to simulations for density and density slopes: this regime is shown to be rapidly reached allowing to get sub-percent precision for a wide range of densities and variances. The corresponding asymptotic limit provides an estimate of the cosmic variance of standard concentric cell statistics applied to finite surveys. More generally, no assumption on the separation is required for some specific moments of the two-point statistics, for instance when predicting the generating function of cumulants containing any powers of concentric densities in one location and one power of density at some arbitrary distance from the rest. This exact `one external leg' cumulant generating function is used in particular to probe the rate of convergence of the large-separation approximation.
Density estimation of small-mammal populations using a trapping web and distance sampling methods
Anderson, David R.; Burnham, Kenneth P.; White, Gary C.; Otis, David L.
1983-01-01
Distance sampling methodology is adapted to enable animal density (number per unit of area) to be estimated from capture-recapture and removal data. A trapping web design provides the link between capture data and distance sampling theory. The estimator of density is D = Mt+1f(0), where Mt+1 is the number of individuals captured and f(0) is computed from the Mt+1 distances from the web center to the traps in which those individuals were first captured. It is possible to check qualitatively the critical assumption on which the web design and the estimator are based. This is a conceptual paper outlining a new methodology, not a definitive investigation of the best specific way to implement this method. Several alternative sampling and analysis methods are possible within the general framework of distance sampling theory; a few alternatives are discussed and an example is given.
International Nuclear Information System (INIS)
Brain metastases (BM) are the most common form of intracranial cancer. The incidence of BM seems to have increased over the past decade. Recursive partitioning analysis (RPA) of data from three Radiation Therapy Oncology Group (RTOG) trials (1200 patients) has allowed three prognostic groups to be identified. More recently a simplified stratification system that uses the evaluation of three main prognostics factors for radiosurgery in BM was developed. To analyze the overall survival rate (OS), prognostic factors affecting outcomes and to estimate the potential improvement in OS for patients with BM from breast cancer, stratified by RPA class and brain metastases score (BS-BM). From January 1996 to December 2004, 174 medical records of patients with diagnosis of BM from breast cancer, who received WBRT were analyzed. The surgery followed by WBRT was used in 15.5% of patients and 84.5% of others patients were submitted at WBRT alone; 108 patients (62.1%) received the fractionation schedule of 30 Gy in 10 fractions. Solitary BM was present in 37.9 % of patients. The prognostic factors evaluated for OS were: age, Karnofsky Performance Status (KPS), number of lesions, localization of lesions, neurosurgery, chemotherapy, absence extracranial disease, RPA class, BS-BM and radiation doses and fractionation. The OS in 1, 2 and 3 years was 33.4 %, 16.7%, and 8.8 %, respectively. The RPA class analysis showed strong relation with OS (p < 0.0001). The median survival time by RPA class in months was: class I 11.7, class II 6.2 and class III 3.0. The significant prognostic factors associated with better OS were: higher KPS (p < 0.0001), neurosurgery (P < 0.0001), single metastases (p = 0.003), BS-BM (p < 0.0001), control primary tumor (p = 0.002) and absence of extracranial metastases (p = 0.001). In multivariate analysis, the factors associated positively with OS were: neurosurgery (p < 0.0001), absence of extracranial metastases (p <0.0001) and RPA class I (p < 0.0001). Our
Density of Jatropha curcas Seed Oil and its Methyl Esters: Measurement and Estimations
Veny, Harumi; Baroutian, Saeid; Aroua, Mohamed Kheireddine; Hasan, Masitah; Raman, Abdul Aziz; Sulaiman, Nik Meriam Nik
2009-04-01
Density data as a function of temperature have been measured for Jatropha curcas seed oil, as well as biodiesel jatropha methyl esters at temperatures from above their melting points to 90 ° C. The data obtained were used to validate the method proposed by Spencer and Danner using a modified Rackett equation. The experimental and estimated density values using the modified Rackett equation gave almost identical values with average absolute percent deviations less than 0.03% for the jatropha oil and 0.04% for the jatropha methyl esters. The Janarthanan empirical equation was also employed to predict jatropha biodiesel densities. This equation performed equally well with average absolute percent deviations within 0.05%. Two simple linear equations for densities of jatropha oil and its methyl esters are also proposed in this study.
A continuous bivariate model for wind power density and wind turbine energy output estimations
International Nuclear Information System (INIS)
The wind power probability density function is useful in both the design process of a wind turbine and in the evaluation process of the wind resource available at a potential site. The continuous probability models used in the scientific literature to estimate the wind power density distribution function and wind turbine energy output assume that air density is independent of the wind speed. A constant annual value for air density of 1.225 kg m-3, corresponding to standard conditions (sea level, 15 oC), is generally used. A bivariate probability model (BPM) is presented in this paper for wind power density and wind turbine energy output estimations. This model takes into account the time variability of air density and wind speed, as well as the correlation existing between both variables. Contingency type bivariate distributions with specified marginal distributions have been used for this purpose. The proposed model is applied in this paper to meteorological data (temperature, pressure, relative humidity, wind speed) recorded over a one year period at a weather station located at the facilities of the Technological Institute of the Canary Islands (Spain). The conclusion reached is that the BPM presented in this paper is more realistic than the univariate probability models (UPMs) normally used in the scientific literature. In the particular case under study, and for all the situations analysed, the BPM has provided values for the annual mean wind power density and annual energy output of a wind turbine that fit the sample data better than the UPMs. However, as a result of the climatological characteristics of the area where the analysis was performed, the results do not differ notably from those obtained through the use of a UPM and the mean air density of the area
Estimation of energy density of Li-S batteries with liquid and solid electrolytes
Li, Chunmei; Zhang, Heng; Otaegui, Laida; Singh, Gurpreet; Armand, Michel; Rodriguez-Martinez, Lide M.
2016-09-01
With the exponential growth of technology in mobile devices and the rapid expansion of electric vehicles into the market, it appears that the energy density of the state-of-the-art Li-ion batteries (LIBs) cannot satisfy the practical requirements. Sulfur has been one of the best cathode material choices due to its high charge storage (1675 mAh g-1), natural abundance and easy accessibility. In this paper, calculations are performed for different cell design parameters such as the active material loading, the amount/thickness of electrolyte, the sulfur utilization, etc. to predict the energy density of Li-S cells based on liquid, polymeric and ceramic electrolytes. It demonstrates that Li-S battery is most likely to be competitive in gravimetric energy density, but not volumetric energy density, with current technology, when comparing with LIBs. Furthermore, the cells with polymer and thin ceramic electrolytes show promising potential in terms of high gravimetric energy density, especially the cells with the polymer electrolyte. This estimation study of Li-S energy density can be used as a good guidance for controlling the key design parameters in order to get desirable energy density at cell-level.
A method to estimate the neutral atmospheric density near the ionospheric main peak of Mars
Zou, Hong; Ye, Yu Guang; Wang, Jin Song; Nielsen, Erling; Cui, Jun; Wang, Xiao Dong
2016-04-01
A method to estimate the neutral atmospheric density near the ionospheric main peak of Mars is introduced in this study. The neutral densities at 130 km can be derived from the ionospheric and atmospheric measurements of the Radio Science experiment on board Mars Global Surveyor (MGS). The derived neutral densities cover a large longitude range in northern high latitudes from summer to late autumn during 3 Martian years, which fills the gap of the previous observations for the upper atmosphere of Mars. The simulations of the Laboratoire de Météorologie Dynamique Mars global circulation model can be corrected with a simple linear equation to fit the neutral densities derived from the first MGS/RS (Radio Science) data sets (EDS1). The corrected simulations with the same correction parameters as for EDS1 match the derived neutral densities from two other MGS/RS data sets (EDS2 and EDS3) very well. The derived neutral density from EDS3 shows a dust storm effect, which is in accord with the Mars Express (MEX) Spectroscopy for Investigation of Characteristics of the Atmosphere of Mars measurement. The neutral density derived from the MGS/RS measurements can be used to validate the Martian atmospheric models. The method presented in this study can be applied to other radio occultation measurements, such as the result of the Radio Science experiment on board MEX.
Fracture density estimates in glaciogenic deposits from P-wave velocity reductions
International Nuclear Information System (INIS)
Subsidence-induced fracturing of glaciogenic deposits over coal mines in the southern Illinois basis alters hydraulic properties of drift aquifers and exposes these aquifers to surface contaminants. In this study, refraction tomography surveys were used in conjunction with a generalized form of a seismic fracture density model to estimate the vertical and lateral extent of fracturing in a 12-m thick overburden of loess, clay, glacial till, and outwash above a longwall coal mine at 90 m depth. This generalized model accurately predicted fracture trends and densities from azimuthal P-wave velocity variations over unsaturated single- and dual-parallel fractures exposed at the surface. These fractures extended at least 6 m and exhibited 10--15 cm apertures at the surface. The pre- and postsubsidence velocity ratios were converted into fracture densities that exhibited qualitative agreement with the observed surface and inferred subsurface fracture distribution. Velocity reductions as large as 25% were imaged over the static tension zone of the mine where fracturing may extend to depths of 10--15 m. Finally, the seismically derived fracture density estimates were plotted as a function of subsidence-induced drawdown across the panel to estimate the average specific storage of the sand and gravel lower drift aquifer. This value was at least 20 times higher than the presubsidence (unfractured) specific storage for the same aquifer
International Nuclear Information System (INIS)
Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.
Energy Technology Data Exchange (ETDEWEB)
Burke, TImothy P. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Kiedrowski, Brian C. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Martin, William R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-11-19
Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.
Estimation of the density of the clay-organic complex in soil
Czyż, Ewa A.; Dexter, Anthony R.
2016-01-01
Soil bulk density was investigated as a function of soil contents of clay and organic matter in arable agricultural soils at a range of locations. The contents of clay and organic matter were used in an algorithmic procedure to calculate the amounts of clay-organic complex in the soils. Values of soil bulk density as a function of soil organic matter content were used to estimate the amount of pore space occupied by unit amount of complex. These estimations show that the effective density of the clay-organic matter complex is very low with a mean value of 0.17 ± 0.04 g ml-1 in arable soils. This value is much smaller than the soil bulk density and smaller than any of the other components of the soil considered separately (with the exception of the gas content). This low value suggests that the clay-soil complex has an extremely porous and open structure. When the complex is considered as a separate phase in soil, it can account for the observed reduction of bulk density with increasing content of organic matter.
Saranphat Suwanrat; Dusit Ngoprasert; Christopher Sutherland; Pongthep Suwanwaree; Tommaso Savini
2015-01-01
Tropical Asian Galliformes are secretive and difficult to survey. Many of these species are considered “at risk” due to habitat degradation although reliable density estimates are lacking. Using camera trapping and distance sampling data collected on the Siamese Fireback (Lophura diardi) in northeastern Thailand, we compared density estimates for pristine and degraded lowland forest. Density was poorly estimated using distance sampling, likely due to small sample size arising from poor visibi...
Efficient Estimation of Dynamic Density Functions with Applications in Streaming Data
Qahtan, Abdulhakim
2016-05-11
Recent advances in computing technology allow for collecting vast amount of data that arrive continuously in the form of streams. Mining data streams is challenged by the speed and volume of the arriving data. Furthermore, the underlying distribution of the data changes over the time in unpredicted scenarios. To reduce the computational cost, data streams are often studied in forms of condensed representation, e.g., Probability Density Function (PDF). This thesis aims at developing an online density estimator that builds a model called KDE-Track for characterizing the dynamic density of the data streams. KDE-Track estimates the PDF of the stream at a set of resampling points and uses interpolation to estimate the density at any given point. To reduce the interpolation error and computational complexity, we introduce adaptive resampling where more/less resampling points are used in high/low curved regions of the PDF. The PDF values at the resampling points are updated online to provide up-to-date model of the data stream. Comparing with other existing online density estimators, KDE-Track is often more accurate (as reflected by smaller error values) and more computationally efficient (as reflected by shorter running time). The anytime available PDF estimated by KDE-Track can be applied for visualizing the dynamic density of data streams, outlier detection and change detection in data streams. In this thesis work, the first application is to visualize the taxi traffic volume in New York city. Utilizing KDE-Track allows for visualizing and monitoring the traffic flow on real time without extra overhead and provides insight analysis of the pick up demand that can be utilized by service providers to improve service availability. The second application is to detect outliers in data streams from sensor networks based on the estimated PDF. The method detects outliers accurately and outperforms baseline methods designed for detecting and cleaning outliers in sensor data. The
Institute of Scientific and Technical Information of China (English)
LI Ning; SHI Tielin
2007-01-01
Blind source Separation and estimation of the number of sources usually demand that the number of sensors should be greater than or equal to that of the sources, which, however, is very difficult to satisfy for the complex Systems. A new estimating method based on power spectral density (PSD) is presented. When the relation between the number of sensors and that of sources is unknown, the PSD matrix is first obtained by the ratio of PSD of the observation signals, and then the bound of the number of correlated sources with common frequencies can be estimated by comparing every column vector of PSD matrix. The effectiveness of the proposed method is verified by theoretical analysis and experiments, and the influence of noise on the estimation of number of source is simulated.
Breast Tissue Composition and Susceptibility to Breast Cancer
Boyd, Norman F.; Lisa J Martin; Bronskill, Michael; Martin J. Yaffe; Duric, Neb; Minkin, Salomon
2010-01-01
Breast density, as assessed by mammography, reflects breast tissue composition. Breast epithelium and stroma attenuate x-rays more than fat and thus appear light on mammograms while fat appears dark. In this review, we provide an overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer. We review the evidence that breast density is a risk factor for breast cancer, the histological and other risk factors that are associat...
A Note on the Estimation of Semiparametric Two-Sample Density Ratio Models
Institute of Scientific and Technical Information of China (English)
Gang YU; Wei GAO; Ningzhong SHI
2012-01-01
In this paper,a semiparametric two-sample density ratio model is considered and the empirical likelihood method is applied to obtain the parameters estimation.A commonly occurring problem in computing is that the empirical likelihood function may be a concaveconvex function.Here a simple Lagrange saddle point algorithm is presented for computing the saddle point of the empirical likelihood function when the Lagrange multiplier has no explicit solution.So we can obtain the maximum empirical likelihood estimation (MELE) of parameters.Monte Carlo simulations are presented to illustrate the Lagrange saddle point algorithm.
International Nuclear Information System (INIS)
Because the glandular content rate is an important factor in evaluating breast cancer detection and average glandular dose, it is important in mammography research to estimate and analyze this rate. The purpose of this study was to obtain a formula for statistical estimation of the glandular content rate, to clarify statistically the influence of age group and compressed breast thickness (CBT) on estimating the glandular content rate, and to show statistically the general relation between glandular content rate and the factors of age and CBT. The subjects were 740 Japanese women aged 20-91 years (mean±SD: 48.3±12.8 years) who had undergone mammography. In our study, the glandular content rate was statistically estimated from age group, mAs-value, and CBT when subjects underwent mammography, from a phantom simulation, and from MR images of the breast. In addition, multivariate analysis was carried to examine statistically the influence of age group and CBT on glandular content rate. The mean glandular content rate as estimated by age group was as follows: 35.6% for those in their 20s, 33.4% in the 30s, 27.5% in the 40s, 23.8% in the 50s, and 21.8% in those 60 and over. The rate for the subjects as a whole was 27.1%. This study indicated that overestimation occurred if the estimated value of the glandular content rate was not corrected in the 3D-measurement by MRI. In addition, this study showed that the statistical influence on glandular content rate was significantly larger for CBT than age. (author)
Lawrence, G.; Wallis, M.; Allgood, P.; Nagtegaal, I.D.; Warwick, J.; Cafferty, F.H.; Houssami, N.; Kearins, O.; Tappenden, N.; O'Sullivan, E.; Duffy, S.W.
2009-01-01
BACKGROUND: Evidence of the impact of breast screening is limited by biases inherent in non-randomised studies and often by lack of complete population data. We address this by estimating the effect of screen detection on cause-specific fatality in breast cancer, corrected for all potential biases,
Pedotransfer functions for Irish soils - estimation of bulk density (ρb) per horizon type
Reidy, B.; Simo, I.; Sills, P.; Creamer, R. E.
2016-01-01
Soil bulk density is a key property in defining soil characteristics. It describes the packing structure of the soil and is also essential for the measurement of soil carbon stock and nutrient assessment. In many older surveys this property was neglected and in many modern surveys this property is omitted due to cost both in laboratory and labour and in cases where the core method cannot be applied. To overcome these oversights pedotransfer functions are applied using other known soil properties to estimate bulk density. Pedotransfer functions have been derived from large international data sets across many studies, with their own inherent biases, many ignoring horizonation and depth variances. Initially pedotransfer functions from the literature were used to predict different horizon type bulk densities using local known bulk density data sets. Then the best performing of the pedotransfer functions were selected to recalibrate and then were validated again using the known data. The predicted co-efficient of determination was 0.5 or greater in 12 of the 17 horizon types studied. These new equations allowed gap filling where bulk density data were missing in part or whole soil profiles. This then allowed the development of an indicative soil bulk density map for Ireland at 0-30 and 30-50 cm horizon depths. In general the horizons with the largest known data sets had the best predictions, using the recalibrated and validated pedotransfer functions.
Directory of Open Access Journals (Sweden)
José Fajardo
2012-12-01
Full Text Available This paper uses the Liu et al. (2007 approach to estimate the optionimplied Risk-Neutral Densities (RND, real-world density (RWD, and relative risk aversion from the Brazilian Real/US Dollar exchange rate distribution. Our empirical application uses a sample of exchange-traded Brazilian Real currency options from 1999 to 2011. Our estimated value of the relative risk aversion is around 2.7, which is in line with other articles for the Brazilian Economy. Our out-of-sample results showed that the RND has some ability to forecast the Brazilian Real exchange rate, but when we incorporate the risk aversion, the out-of-sample performance improves substantially.
Stewart, Robert; White, Devin; Urban, Marie; Morton, April; Webster, Clayton; Stoyanov, Miroslav; Bright, Eddie; Bhaduri, Budhendra L.
2013-05-01
The Population Density Tables (PDT) project at Oak Ridge National Laboratory (www.ornl.gov) is developing population density estimates for specific human activities under normal patterns of life based largely on information available in open source. Currently, activity-based density estimates are based on simple summary data statistics such as range and mean. Researchers are interested in improving activity estimation and uncertainty quantification by adopting a Bayesian framework that considers both data and sociocultural knowledge. Under a Bayesian approach, knowledge about population density may be encoded through the process of expert elicitation. Due to the scale of the PDT effort which considers over 250 countries, spans 50 human activity categories, and includes numerous contributors, an elicitation tool is required that can be operationalized within an enterprise data collection and reporting system. Such a method would ideally require that the contributor have minimal statistical knowledge, require minimal input by a statistician or facilitator, consider human difficulties in expressing qualitative knowledge in a quantitative setting, and provide methods by which the contributor can appraise whether their understanding and associated uncertainty was well captured. This paper introduces an algorithm that transforms answers to simple, non-statistical questions into a bivariate Gaussian distribution as the prior for the Beta distribution. Based on geometric properties of the Beta distribution parameter feasibility space and the bivariate Gaussian distribution, an automated method for encoding is developed that responds to these challenging enterprise requirements. Though created within the context of population density, this approach may be applicable to a wide array of problem domains requiring informative priors for the Beta distribution.
Garde, Ainara; Karlen, Walter; Ansermino, J Mark; Dumont, Guy A.
2014-01-01
The photoplethysmogram (PPG) obtained from pulse oximetry measures local variations of blood volume in tissues, reflecting the peripheral pulse modulated by heart activity, respiration and other physiological effects. We propose an algorithm based on the correntropy spectral density (CSD) as a novel way to estimate respiratory rate (RR) and heart rate (HR) from the PPG. Time-varying CSD, a technique particularly well-suited for modulated signal patterns, is applied to the PPG. The respiratory...
Density estimation and adaptive bandwidths: A primer for public health practitioners
Tanski Susanne; Sargent James; Shi Xun; Carlos Heather A; Berke Ethan M
2010-01-01
Abstract Background Geographic information systems have advanced the ability to both visualize and analyze point data. While point-based maps can be aggregated to differing areal units and examined at varying resolutions, two problems arise 1) the modifiable areal unit problem and 2) any corresponding data must be available both at the scale of analysis and in the same geographic units. Kernel density estimation (KDE) produces a smooth, continuous surface where each location in the study area...
Use of Camera-Trapping to Estimate Puma Density and Influencing Factors in Central Brazil
Negroes, Nuno; Sarmento, Pedro; Cruz, Joana; Eira, Catarina; Revilla, Eloy; Fonseca, Carlos; Torres, Natália M.; Furtado, Mariana M.; Sollmann, Rahel
2010-01-01
We used remotely triggered cameras to collect data on Puma (Puma concolor) abundance and occupancy in an area of tropical forest in Brazil where the species’ status is poorly known. To evaluate factors influencing puma occupancy we used data from 5 sampling campaigns in 3 consecutive years (2005 to 2007) and 2 seasons (wet and dry), at a state park and a private forest reserve. We estimated puma numbers and density for the 2007 sampling data by developing a standardized individua...
An elegant method to estimate helium-like ion densities from visible and VUV plasma spectroscopy
Rachlew, Elisabeth
1993-01-01
A method is presented to estimate the densities of He-like carbon and oxygen ions from the observation of the Li-like 3p + 3s transitions inthe visible and the 3p + 2s transitions in the vacuum ulbaviolet The method is based on a zerodimensional model for plasmas with short particle confinement times. General coefficients for this study are derived and evaluated numerically. The method is applied to Extrap-T1 reversed field pinch data
Directory of Open Access Journals (Sweden)
Mahdi Emadi
2013-02-01
Full Text Available We consider n observations from the GARCH-type model: Z = UY, where U and Y are independent random variables. We aim to estimate density function Y where Y have a weighted distribution. We determine a sharp upper bound of the associated mean integrated square error. We also make use of the measure of expected true evidence, so as to determine when model leads to a crisis and causes data to be lost.
Dillon, A.; Kelly, M J
2007-01-01
We used remote cameras to obtain information on an elusive species and to examine the effects of different camera trapping methodologies on abundance estimates. We determined activity pattern, trail use, trap success, and density of ocelot Leopardus pardalis in seven camera-trap surveys across two habitat types in western Belize: tropical broad-leaf rainforest and tropical pine forest. Ocelots in the rainforest were active mostly at night, in particular immediately after sunset, and they trav...
Gonzalez, Raelvim
2010-01-01
Ultrasonic Consolidation of stainless steel structures is being investigated for potential applications. This study investigates the suitability of Stainless Steel 316L annealed (SS316L annealed) as a building material for Ultrasonic Consolidation (UC), including research on Linear Welding Density (LWD) estimation on micrographs of samples. Experiment results are presented that include the effect of UC process parameters on SS316L annealed UC, optimum levels of these parameters, and bond qual...
Kernel Density Estimation of Tropical Cyclone Frequencies in the North Atlantic Basin
Timothy A. Joyner; Robert V. Rohli
2010-01-01
Previous research has identified specific areas of frequent tropical cyclone activity in the North Atlantic basin. This study examines long-term and decadal spatio-temporal patterns of Atlantic tropical cyclone frequencies from 1944 to 2009, and analyzes categorical and decadal centroid patterns using kernel density estimation (KDE) and centrographic statistics. Results corroborate previous research which has suggested that the Bermuda-Azores anticyclone plays an integral role in the directio...
NEAR INFRARED SPECTROSCOPY FOR ESTIMATING SUGARCANE BAGASSE CONTENT IN MEDIUM DENSITY FIBERBOARD
Ugo Leandro Belini; Paulo Ricardo Gherardi Hein; Mario Tomazello Filho Mail; José Carlos Rodrigues; Gilles Chaix
2011-01-01
Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus ...
SENSITIVITY ANALYSIS AND DENSITY ESTIMATION FOR THE HOBSON-ROGERS STOCHASTIC VOLATILITY MODEL
REIICHIRO KAWAI
2009-01-01
Monte Carlo estimators of sensitivity indices and the marginal density of the price dynamics are derived for the Hobson-Rogers stochastic volatility model. Our approach is based mainly upon the Kolmogorov backward equation by making full use of the Markovian property of the dynamics given the past information. Some numerical examples are presented with a GARCH-like volatility function and its extension to illustrate the effectiveness of our formulae together with a clear exhibition of the ske...
Kernel Density Feature Points Estimator for Content-Based Image Retrieval
Zuva, Tranos; Ojo, Sunday O; Ngwira, Seleman M
2012-01-01
Research is taking place to find effective algorithms for content-based image representation and description. There is a substantial amount of algorithms available that use visual features (color, shape, texture). Shape feature has attracted much attention from researchers that there are many shape representation and description algorithms in literature. These shape image representation and description algorithms are usually not application independent or robust, making them undesirable for generic shape description. This paper presents an object shape representation using Kernel Density Feature Points Estimator (KDFPE). In this method, the density of feature points within defined rings around the centroid of the image is obtained. The KDFPE is then applied to the vector of the image. KDFPE is invariant to translation, scale and rotation. This method of image representation shows improved retrieval rate when compared to Density Histogram Feature Points (DHFP) method. Analytic analysis is done to justify our m...
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In this paper we discuss representations of charge particle densities in particle-in-cell (PIC) simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2d code of Bassi, designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform (TFCT); and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into Bassi's CSR code, and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.
Energy Technology Data Exchange (ETDEWEB)
Balsa Terzic, Gabriele Bassi
2011-07-01
In this paper we discuss representations of charge particle densities in particle-in-cell (PIC) simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2d code of Bassi, designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform (TFCT); and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into Bassi's CSR code, and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.
International Nuclear Information System (INIS)
Fractures as the most common and important geological features have a significant share in reservoir fluid flow. Therefore, fracture detection is one of the important steps in fractured reservoir characterization. Different tools and methods are introduced for fracture detection from which formation image logs are considered as the common and effective tools. Due to the economical considerations, image logs are available for a limited number of wells in a hydrocarbon field. In this paper, we suggest a model to estimate fracture density from the conventional well logs using an adaptive neuro-fuzzy inference system. Image logs from two wells of the Asmari formation in one of the SW Iranian oil fields are used to verify the results of the model. Statistical data analysis indicates good correlation between fracture density and well log data including sonic, deep resistivity, neutron porosity and bulk density. The results of this study show that there is good agreement (correlation coefficient of 98%) between the measured and neuro-fuzzy estimated fracture density
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Quantitation of cell density in tissues has proven problematic over the years. The manual microscopic methodology, where an investigator visually samples multiple areas within slides of tissue sections, has long remained the basic ‘standard’ for many studies and for routine histopathologic reporting. Nevertheless, novel techniques that may provide a more standardized approach to quantitation of cells in tissue sections have been made possible by computerized video image analysis methods over recent years. The present study describes a novel, computer-assisted video image analysis method of quantitating immunostained cells within tissue sections, providing continuous graphical data. This technique enables the measurement of both distribution and density of cells within tissue sections. Specifically, the study considered immunoperoxidase-stained tumor infiltrating lymphocytes within breast tumor specimens, using the number of immunostained pixels within tissue sections to determine cellular density and number. Comparison was made between standard manual graded quantitation methods and video image analysis, using the same tissue sections. The study demonstrates that video image techniques and computer analysis can provide continuous data on cell density and number in immunostained tissue sections, which compares favorably with standard visual quantitation methods, and may offer an alternative
Carroll, Raymond J.
2011-03-01
In many applications we can expect that, or are interested to know if, a density function or a regression curve satisfies some specific shape constraints. For example, when the explanatory variable, X, represents the value taken by a treatment or dosage, the conditional mean of the response, Y , is often anticipated to be a monotone function of X. Indeed, if this regression mean is not monotone (in the appropriate direction) then the medical or commercial value of the treatment is likely to be significantly curtailed, at least for values of X that lie beyond the point at which monotonicity fails. In the case of a density, common shape constraints include log-concavity and unimodality. If we can correctly guess the shape of a curve, then nonparametric estimators can be improved by taking this information into account. Addressing such problems requires a method for testing the hypothesis that the curve of interest satisfies a shape constraint, and, if the conclusion of the test is positive, a technique for estimating the curve subject to the constraint. Nonparametric methodology for solving these problems already exists, but only in cases where the covariates are observed precisely. However in many problems, data can only be observed with measurement errors, and the methods employed in the error-free case typically do not carry over to this error context. In this paper we develop a novel approach to hypothesis testing and function estimation under shape constraints, which is valid in the context of measurement errors. Our method is based on tilting an estimator of the density or the regression mean until it satisfies the shape constraint, and we take as our test statistic the distance through which it is tilted. Bootstrap methods are used to calibrate the test. The constrained curve estimators that we develop are also based on tilting, and in that context our work has points of contact with methodology in the error-free case.
Energy Technology Data Exchange (ETDEWEB)
Donovan, E. M.; James, H.; Bonora, M.; Yarnold, J. R.; Evans, P. M. [Joint Department of Physics, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton SM2 5PT (United Kingdom); Physics Department, Ipswich Hospital NHS Foundation Trust, Ipswich IP4 5PD (United Kingdom); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT, United Kingdom and School of Radiotherapy, University of Milan, Milan 20122 (Italy); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT (United Kingdom); Centre for Vision Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom)
2012-10-15
contralateral breast doses and LAR were comparable to WBRT, despite their added complexity. The smaller irradiated volume of the ABPI plan contributed to a halving of LAR for contralateral breast compared with the other plan types. Daily image guided radiotherapy (IGRT) for a left breast protocol using kilovoltage CBCT contributed <10% to LAR for the majority of organs, and did not exceed 22% of total organ dose. Conclusions: Phantom measurements and calculations of LAR from the BEIR VII models predict that complex breast radiotherapy techniques do not increase the theoretical risk of second cancer incidence for organs distant from the treated breast, or the contralateral breast where appropriate plan constraints are applied. Complex SIB treatments are predicted to increase the risk of second cancer incidence in the lungs compared to standard whole breast radiotherapy; this is outweighed by the threefold reduction in 5 yr local recurrence risk for patients of high risk of recurrence, and young age, from the use of radiotherapy. APBI may have a favorable impact on risk of second cancer in the contralateral breast and lung for older patients at low risk of recurrence. Intensive use of IGRTincreased the estimated values of LAR but these are dominated by the effect of the dose from the radiotherapy, and any increase in LAR from IGRT is much lower than the models' uncertainties.
International Nuclear Information System (INIS)
The aim of the work is to assess the probability of the breast cancer occurrence on the basis of analysis of the clinical and mammographical factors in women with unpalpable breast tumor. In the period from the 1st February 1995 to the 31st August 2000, 163 surgical procedures for the removal of any lesions in the breasts were conducted, after being previously marked by localized needle, in women who earlier underwent mammography exam.Following data was taken into consideration: patients age, type of the breast structure; side of the breast, where the lesion was localized in the mammography exam; localized lesions depending on the quadrant; shape of the lesion; size of the lesion in millimeters; presence and the type of microcalcifications. 1. The only one population factor, which can be distinguished as characteristic for the women suffering from the breast cancer impalpable in clinical testing, is the age of the patient, because the breast cancer in these women more frequently occurs after 53 years of age. 2. On the basis of our own material the following radiological symptoms characteristic for the breast cancer in mammography exam were stated: the breast cancer is more frequently found in the upper external quadrant; all lesions, which in mammography exam were identified as multifocal and radiologically suspected in histopathology exam turned out to be the cancer; pleomorphic microcalcifications are characteristic for the malignant lesions; external outline and the shape of the lesion are the features, which allow to differentiate malignant and benign lesions. 3. The analysis of the material indicates that the greatest probability of the breast cancer occurrence is in case of the four risk factors occurrence simultaneously, and the smallest in case of only one risk factor occurrence. (author)
International Nuclear Information System (INIS)
The validation of diagnostic date from a nuclear fusion experiment is an important issue. The concept of an Integrated Data Analysis (IDA) allows the consistent estimation of plasma parameters from heterogeneous data sets. Here, the determination of the ion effective charge (Zeff) is considered. Several diagnostic methods exist for the determination of Zeff, but the results are in general not in agreement. In this work, the problem of Zeff estimation on the TEXTOR tokamak is approached from the perspective of IDA, in the framework of Bayesian probability theory. The ultimate goal is the estimation of a full Zeff profile that is consistent both with measured bremsstrahlung emissivities, as well as individual impurity spectral line intensities obtained from Charge Exchange Recombination Spectroscopy (CXRS). We present an overview of the various uncertainties that enter the calculation of a Zeff profile from bremsstrahlung date on the one hand, and line intensity data on the other hand. We discuss a simple linear and nonlinear Bayesian model permitting the estimation of a central value for Zeff and the electron density ne on TEXTOR from bremsstrahlung emissivity measurements in the visible, and carbon densities derived from CXRS. Both the central Zeff and ne are sampled using an MCMC algorithm. An outlook is given towards possible model improvements
Malkovsky, V. I.; Pek, A. A.
2007-06-01
The convective transfer of radionuclides by subsurface water from a geological repository of solidified high-level radioactive wastes (HLW) is considered. The repository is a cluster of wells of large diameter with HLW disposed of in the lower portions of the wells. The safe distance between wells as a function of rock properties and parameters of well loading with wastes has been estimated from mathematical modeling. A maximum permissible concentration of radionuclides in subsurface water near the ground surface above the repository is regarded as a necessary condition of safety. The estimates obtained show that well repositories allow for a higher density of solid HLW disposal than shaft storage facilities. Advantages and disadvantages of both types of storage facilities are considered in order to estimate the prospects for their use for underground disposal of solid HLW.
Sadeh, Iftach; Lahav, Ofer
2015-01-01
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister and Lahav (2004). Large photometric galaxy surveys are important for cosmological studies, and in particular for characterizing the nature of dark energy. The success of such surveys greatly depends on the ability to measure photo-zs, based on limited spectral data. ANNz2 utilizes multiple machine learning methods, such as artificial neural networks, boosted decision/regression trees and k-nearest neighbours. The objective of the algorithm is to dynamically optimize the performance of the photo-z estimation, and to properly derive the associated uncertainties. In addition to single-value solutions, the new code also generates full probability density functions (PDFs) in two different ways. In addition, estimators are incorporated to mitigate possible problems of spectroscopic training samples which are not representative or are incomplete. ANNz2 is also adapted to provide optimized solution...
Density and Population Estimation of the Bornean Elephants (Elephas maximus borneensis in Sabah
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Raymond Alfred
2010-01-01
Full Text Available Problem statement: In Asia, four elephant subspecies have been identified, Elephas maximus maximus from Sri Lanka, Elephas maximus summatranus from Sumatra, Elephas maximus borneensis (based on recent DNA analysis from Borneo and Elephas maximus indicus, from mainland Asia. The Bornean elephant has a limited distribution and is found only in the northeastern part of the island, (Malaysian Sabah and Indonesian Kalimantan. Previous estimations for the population in Sabah have ranged between 500-2000 elephants. These estimations have been carried out through a non-systematic approach, either via interview or from direct sightings or extrapolating population count data from limited sites. In order to prepare the conservation plan for this species in Sabah, there is a need to establish reliable information on their density and population size. The main objective of this study was to determine the elephant density and population size in five main elephant managed ranges in Sabah. Approach: In this study, relative distribution and spatial density of the Bornean elephant was developed and established, using a systematic line transect survey and a long term monitoring of dung decay rates. We conducted the elephant population census in Sabah between July 2007 and December 2008. Using a line-transect dung-count methodology, we surveyed 216 line transects; with a total distance of 186.12 km, in five main elephant managed ranges. Namely (i Tabin Wildlife Reserve, (ii Lower Kinabatangan, (iii Central Forest, (iv North Kinabatangan and (v Ulu Kalumpang. Results: We presented the elephant density estimate using long term monitoring of dung decay rates. In each range, the elephants density varied depending on the size of the suitable habitat. The size of the suitable habitat was derived from WWFs study report (WWF-Malaysia, 2008. Densities were analyzed following line-transect analysis guidelines and were computed using the software Distance v6.0. Conclusion
mBEEF-vdW: Robust fitting of error estimation density functionals
Lundgaard, Keld T.; Wellendorff, Jess; Voss, Johannes; Jacobsen, Karsten W.; Bligaard, Thomas
2016-06-01
We propose a general-purpose semilocal/nonlocal exchange-correlation functional approximation, named mBEEF-vdW. The exchange is a meta generalized gradient approximation, and the correlation is a semilocal and nonlocal mixture, with the Rutgers-Chalmers approximation for van der Waals (vdW) forces. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012), 10.1103/PhysRevB.85.235149; J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014), 10.1063/1.4870397]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function, reducing the sensitivity to outliers in the datasets. To more reliably determine the optimal model complexity, we furthermore introduce a generalization of the bootstrap 0.632 estimator with hierarchical bootstrap sampling and geometric mean estimator over the training datasets. Using this estimator, we show that the robust loss function leads to a 10 % improvement in the estimated prediction error over the previously used least-squares loss function. The mBEEF-vdW functional is benchmarked against popular density functional approximations over a wide range of datasets relevant for heterogeneous catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show the potential-energy curve of graphene on the nickel(111) surface, where mBEEF-vdW matches the experimental binding length. mBEEF-vdW is currently available in gpaw and other density functional theory codes through Libxc, version 3.0.0.
Dynamics and density estimation of hydroxyl radicals in a pulsed corona discharge
International Nuclear Information System (INIS)
Hydroxyl radicals generated by a pulsed corona discharge are measured by laser-induced fluorescence (LIF) with a tunable KrF excimer laser. The discharge with 35 kV voltage and 100 ns pulse current occurs between needle and plate electrodes in H2O/O2/N2 mixture at atmospheric pressure. The density and decay profile of OH radicals are studied. OH radicals decay with time after the discharge with a time constant of about 30-60 μs. The OH density is estimated to be about 7x1014 cm-3 in H2O(2.4%)/N2 mixture 10 μs after the discharge. The OH density is approximately proportional to the energy dissipated in the discharge. The O2 content influences the OH production. When the O2 content is varied in H2O(2.4%)/O2/N2 mixture, the OH density is maximum at an O2 content of 2%. The spatial distribution of OH density shows that OH radicals are produced in the streamers under positive discharge. (author)
Directory of Open Access Journals (Sweden)
Tara Chestnut
Full Text Available Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd, is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L(-1. The highest density observed was ∼3 million zoospores L(-1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free
Chestnut, Tara E.; Anderson, Chauncey; Popa, Radu; Blaustein, Andrew R.; Voytek, Mary; Olson, Deanna H.; Kirshtein, Julie
2014-01-01
Biodiversity losses are occurring worldwide due to a combination of stressors. For example, by one estimate, 40% of amphibian species are vulnerable to extinction, and disease is one threat to amphibian populations. The emerging infectious disease chytridiomycosis, caused by the aquatic fungus Batrachochytrium dendrobatidis (Bd), is a contributor to amphibian declines worldwide. Bd research has focused on the dynamics of the pathogen in its amphibian hosts, with little emphasis on investigating the dynamics of free-living Bd. Therefore, we investigated patterns of Bd occupancy and density in amphibian habitats using occupancy models, powerful tools for estimating site occupancy and detection probability. Occupancy models have been used to investigate diseases where the focus was on pathogen occurrence in the host. We applied occupancy models to investigate free-living Bd in North American surface waters to determine Bd seasonality, relationships between Bd site occupancy and habitat attributes, and probability of detection from water samples as a function of the number of samples, sample volume, and water quality. We also report on the temporal patterns of Bd density from a 4-year case study of a Bd-positive wetland. We provide evidence that Bd occurs in the environment year-round. Bd exhibited temporal and spatial heterogeneity in density, but did not exhibit seasonality in occupancy. Bd was detected in all months, typically at less than 100 zoospores L−1. The highest density observed was ∼3 million zoospores L−1. We detected Bd in 47% of sites sampled, but estimated that Bd occupied 61% of sites, highlighting the importance of accounting for imperfect detection. When Bd was present, there was a 95% chance of detecting it with four samples of 600 ml of water or five samples of 60 mL. Our findings provide important baseline information to advance the study of Bd disease ecology, and advance our understanding of amphibian exposure to free-living Bd in aquatic
Crowe, D.E.; Longshore, K.M.
2010-01-01
We estimated relative abundance and density of Western Burrowing Owls (Athene cunicularia hypugaea) at two sites in the Mojave Desert (200304). We made modifications to previously established Burrowing Owl survey techniques for use in desert shrublands and evaluated several factors that might influence the detection of owls. We tested the effectiveness of the call-broadcast technique for surveying this species, the efficiency of this technique at early and late breeding stages, and the effectiveness of various numbers of vocalization intervals during broadcasting sessions. Only 1 (3) of 31 initial (new) owl responses was detected during passive-listening sessions. We found that surveying early in the nesting season was more likely to produce new owl detections compared to surveying later in the nesting season. New owls detected during each of the three vocalization intervals (each consisting of 30 sec of vocalizations followed by 30 sec of silence) of our broadcasting session were similar (37, 40, and 23; n 30). We used a combination of detection trials (sighting probability) and double-observer method to estimate the components of detection probability, i.e., availability and perception. Availability for all sites and years, as determined by detection trials, ranged from 46.158.2. Relative abundance, measured as frequency of occurrence and defined as the proportion of surveys with at least one owl, ranged from 19.232.0 for both sites and years. Density at our eastern Mojave Desert site was estimated at 0.09 ?? 0.01 (SE) owl territories/km2 and 0.16 ?? 0.02 (SE) owl territories/km2 during 2003 and 2004, respectively. In our southern Mojave Desert site, density estimates were 0.09 ?? 0.02 (SE) owl territories/km2 and 0.08 ?? 0.02 (SE) owl territories/km 2 during 2004 and 2005, respectively. ?? 2010 The Raptor Research Foundation, Inc.
Directory of Open Access Journals (Sweden)
Yongjun Ahn
Full Text Available The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station's density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive
Soil Organic Carbon Density in Hebei Province, China:Estimates and Uncertainty
Institute of Scientific and Technical Information of China (English)
ZHAO Yong-Cun; SHI Xue-Zheng; YU Dong-Sheng; T. F. PAGELLA; SUN Wei-Xia; XU Xiang-Hua
2005-01-01
In order to improve the precision of soil organic carbon (SOC) estimates, the sources of uncertainty in soil organic carbon density (SOCD) estimates and SOC stocks were examined using 363 soil profiles in Hebei Province, China, with three methods: the soil profile statistics (SPS), GIS-based soil type (GST), and kriging interpolation (KI). The GST method, utilizing both pedological professional knowledge and GIS technology, was considered the most accurate method of the three estimations, with SOCD estimates for SPS 10% lower and KI 10% higher. The SOCD range for GST was 84% wider than KI as KI smoothing effect narrowed the SOCD range. Nevertheless, the coefficient of variation for SOCD with KI (41.7%) was less than GST and SPS. Comparing SOCD's lower estimates for SPS versus GST, the major sources of uncertainty were the conflicting area of proportional relations. Meanwhile, the fewer number of soil profiles and the necessity of using the smoothing effect with KI were its sources of uncertainty. Moreover, for local detailed variations of SOCD, GST was more advantageous in reflecting the distribution pattern than KI.
Inamdar, Padmanabh; Mehta, Garima
2011-01-01
Despite advances in management of breast cancer, etiology is still elusive. Diet, obesity and other life style factors have been implicated in its etiology. We assessed the role of obesity and HDL-C levels in patients with rural background in etiology of breast cancer. To know the relation between obesity and incidence of breast cancer in local population. Also to know serum HDL-C level in breast cancer and its correlation with breast cancer. A nested pilot study of 50 breast cancer patients ...
Large-sample study of the kernel density estimators under multiplicative censoring
Asgharian, Masoud; Fakoor, Vahid; 10.1214/11-AOS954
2012-01-01
The multiplicative censoring model introduced in Vardi [Biometrika 76 (1989) 751--761] is an incomplete data problem whereby two independent samples from the lifetime distribution $G$, $\\mathcal{X}_m=(X_1,...,X_m)$ and $\\mathcal{Z}_n=(Z_1,...,Z_n)$, are observed subject to a form of coarsening. Specifically, sample $\\mathcal{X}_m$ is fully observed while $\\mathcal{Y}_n=(Y_1,...,Y_n)$ is observed instead of $\\mathcal{Z}_n$, where $Y_i=U_iZ_i$ and $(U_1,...,U_n)$ is an independent sample from the standard uniform distribution. Vardi [Biometrika 76 (1989) 751--761] showed that this model unifies several important statistical problems, such as the deconvolution of an exponential random variable, estimation under a decreasing density constraint and an estimation problem in renewal processes. In this paper, we establish the large-sample properties of kernel density estimators under the multiplicative censoring model. We first construct a strong approximation for the process $\\sqrt{k}(\\hat{G}-G)$, where $\\hat{G}$ is...
Estimation of graphite density and mechanical strength variation of VHTR during air-ingress accident
International Nuclear Information System (INIS)
An air-ingress accident in a Very High Temperature Gas-Cooled Reactor (VHTR) is anticipated to cause severe changes to graphite density and mechanical strength by an oxidation process that has many side effects. However, quantitative estimations have not yet been performed. This study focuses on predicting the changes in graphite density and mechanical strength via thermal hydraulic system analysis code. In order to analyze the change in graphite density, a simple graphite burn-off model was developed. The model is based on the similarities between a parallel electrical circuit and graphite oxidation. It was used to determine overall changes in the graphite's geometry and density. The model was validated by comparing its results to experimental data that was obtained for several temperatures. In the experiment, cylindrically shaped graphite specimens were oxidized in an electrical furnace and the variations of its mass were measured against time. The experiment's range covered temperatures between 6000 C and 9000 C. Experimental data validated the model's accuracy. Finally, the developed model along with other comprehensive graphite oxidation models was integrated into the VHTR system analysis code, GAMMA. GT-MHR 600 MWt reactor was selected as a reference reactor. Based on the calculation, the main oxidation process was observed 5.5 days after the accident when followed by natural convection. The core maximum temperature reached 16000 C, but never exceeded the maximum temperature criteria, 18000 C. However, the oxidation process did significantly decrease the density of bottom reflector, making it vulnerable to mechanical stress. The stress on the bottom reflector is greatly increased because it sustains the reactor core. The calculation proceeded until 11 days after the accident, resulting in an observed 4.5% decrease in density and a 25% reduction of mechanical strength
A maximum volume density estimator generalised over a proper motion limited sample
Lam, M C; Hambly, N C
2015-01-01
The traditional Schmidt density estimator has been proven to be unbiased and effective in a magnitude limited sample. Previously, efforts have been made to generalise it for populations with non-uniform density and proper motion limited cases. This work shows that the then good assumptions for a proper motion limited sample are no longer sufficient to cope with modern data. Populations with larger differences in the kinematics as compared to the Local Standard of Rest are most severely affected. We show that this systematic bias can be removed by treating the discovery fraction inseparable from the generalised maximum volume integrand. The treatment can be applied to any proper motion limited sample with good knowledge of the kinematics. This work demonstrates the method through application to a mock catalogue of a white dwarf-only solar neighbourhood for various scenarios and compared against the traditional treatment using a survey with Pan-STARRS-like characteristics.
Terzić, Balša; Bassi, Gabriele
2011-07-01
In this paper we discuss representations of charge particle densities in particle-in-cell simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2D code of Bassi et al. [G. Bassi, J. A. Ellison, K. Heinemann, and R. Warnock, Phys. Rev. ST Accel. Beams 12, 080704 (2009); PRABFM1098-440210.1103/PhysRevSTAB.12.080704G. Bassi and B. Terzić, in Proceedings of the 23rd Particle Accelerator Conference, Vancouver, Canada, 2009 (IEEE, Piscataway, NJ, 2009), TH5PFP043], designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform; and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into the CSR code [G. Bassi, J. A. Ellison, K. Heinemann, and R. Warnock, Phys. Rev. ST Accel. Beams 12, 080704 (2009)PRABFM1098-440210.1103/PhysRevSTAB.12.080704], and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.
International Nuclear Information System (INIS)
In this paper we discuss representations of charge particle densities in particle-in-cell simulations, analyze the sources and profiles of the intrinsic numerical noise, and present efficient methods for their removal. We devise two alternative estimation methods for charged particle distribution which represent significant improvement over the Monte Carlo cosine expansion used in the 2D code of Bassi et al. (G. Bassi, J.A. Ellison, K. Heinemann and R. Warnock Phys. Rev. ST Accel. Beams 12 080704 (2009)G. Bassi and B. Terzic, in Proceedings of the 23rd Particle Accelerator Conference, Vancouver, Canada, 2009 (IEEE, Piscataway, NJ, 2009), TH5PFP043), designed to simulate coherent synchrotron radiation (CSR) in charged particle beams. The improvement is achieved by employing an alternative beam density estimation to the Monte Carlo cosine expansion. The representation is first binned onto a finite grid, after which two grid-based methods are employed to approximate particle distributions: (i) truncated fast cosine transform; and (ii) thresholded wavelet transform (TWT). We demonstrate that these alternative methods represent a staggering upgrade over the original Monte Carlo cosine expansion in terms of efficiency, while the TWT approximation also provides an appreciable improvement in accuracy. The improvement in accuracy comes from a judicious removal of the numerical noise enabled by the wavelet formulation. The TWT method is then integrated into the CSR code (G. Bassi, J.A. Ellison, K. Heinemann and R. Warnock Phys. Rev. ST Accel. Beams 12 080704 (2009)), and benchmarked against the original version. We show that the new density estimation method provides a superior performance in terms of efficiency and spatial resolution, thus enabling high-fidelity simulations of CSR effects, including microbunching instability.
Tenreiro, Carlos
1998-01-01
In this paper we consider the weighted average square error An([pi]) = (1/n) [Sigma]nj=1{fn(Xj) -; f(Xj)}2[pi](Xj), where f is the common density function of the independent and identically distributed random vectors X1,..., Xn, fn is the kernel estimator based on these vectors and [pi] is a weight function. Using U-statistics techniques and the results of Gouriéroux and Tenreiro (Preprint 9617, Departamento de Matemática, Universidade de Coimbra, 1996), we establish a central limit theorem f...
Smooth estimation of a monotone hazard and a monotone density under random censoring
Lopuhaä, Hendrik P.; Musta, Eni
2015-01-01
We consider kernel smoothed Grenander-type estimators for a monotone hazard rate and a monotone density in the presence of randomly right censored data. We show that they converge at rate $n^{2/5}$ and that the limit distribution at a fixed point is Gaussian with explicitly given mean and variance. It is well-known that standard kernel smoothing leads to inconsistency problems at the boundary points. It turns out that, also by using a boundary correction, we can only establish uniform consist...
DEFF Research Database (Denmark)
Rosholm, A; Hyldstrup, L; Backsgaard, L; Grunkin, M; Thodberg, H H
2002-01-01
A new automated radiogrammetric method to estimate bone mineral density (BMD) from a single radiograph of the hand and forearm is described. Five regions of interest in radius, ulna and the three middle metacarpal bones are identified and approximately 1800 geometrical measurements from these bones...... BMDDXR was observed to be 0.60% in a clinical study of 24 women and the in vitro variation over 12 different radiological clinics was found to be 1% of the young normal BMDDXR level. In a cohort of 416 women BMDDXR was found to be closely correlated with BMD at the distal forearm measured by dual...
Efficient 3D movement-based kernel density estimator and application to wildlife ecology
Tracey-PR, Jeff; Sheppard, James K.; Lockwood, Glenn K.; Chourasia, Amit; Tatineni, Mahidhar; Fisher, Robert N.; Sinkovits, Robert S.
2014-01-01
We describe an efficient implementation of a 3D movement-based kernel density estimator for determining animal space use from discrete GPS measurements. This new method provides more accurate results, particularly for species that make large excursions in the vertical dimension. The downside of this approach is that it is much more computationally expensive than simpler, lower-dimensional models. Through a combination of code restructuring, parallelization and performance optimization, we were able to reduce the time to solution by up to a factor of 1000x, thereby greatly improving the applicability of the method.
Image denoising via Bayesian estimation of local variance with Maxwell density prior
Kittisuwan, Pichid
2015-10-01
The need for efficient image denoising methods has grown with the massive production of digital images and movies of all kinds. The distortion of images by additive white Gaussian noise (AWGN) is common during its processing and transmission. This paper is concerned with dual-tree complex wavelet-based image denoising using Bayesian techniques. Indeed, one of the cruxes of the Bayesian image denoising algorithms is to estimate the local variance of the image. Here, we employ maximum a posteriori (MAP) estimation to calculate local observed variance with Maxwell density prior for local observed variance and Gaussian distribution for noisy wavelet coefficients. Evidently, our selection of prior distribution is motivated by analytical and computational tractability. The experimental results show that the proposed method yields good denoising results.
Bayesian semiparametric power spectral density estimation in gravitational wave data analysis
Edwards, Matthew C; Christensen, Nelson
2015-01-01
The standard noise model in gravitational wave (GW) data analysis assumes detector noise is stationary and Gaussian distributed, with a known power spectral density (PSD) that is usually estimated using clean off-source data. Real GW data often depart from these assumptions, and misspecified parametric models of the PSD could result in misleading inferences. We propose a Bayesian semiparametric approach to improve this. We use a nonparametric Bernstein polynomial prior on the PSD, with weights attained via a Dirichlet process distribution, and update this using the Whittle likelihood. Posterior samples are obtained using a Metropolis-within-Gibbs sampler. We simultaneously estimate the reconstruction parameters of a rotating core collapse supernova GW burst that has been embedded in simulated Advanced LIGO noise. We also discuss an approach to deal with non-stationary data by breaking longer data streams into smaller and locally stationary components.
Edwards, Matthew C.; Meyer, Renate; Christensen, Nelson
2015-09-01
The standard noise model in gravitational wave (GW) data analysis assumes detector noise is stationary and Gaussian distributed, with a known power spectral density (PSD) that is usually estimated using clean off-source data. Real GW data often depart from these assumptions, and misspecified parametric models of the PSD could result in misleading inferences. We propose a Bayesian semiparametric approach to improve this. We use a nonparametric Bernstein polynomial prior on the PSD, with weights attained via a Dirichlet process distribution, and update this using the Whittle likelihood. Posterior samples are obtained using a blocked Metropolis-within-Gibbs sampler. We simultaneously estimate the reconstruction parameters of a rotating core collapse supernova GW burst that has been embedded in simulated Advanced LIGO noise. We also discuss an approach to deal with nonstationary data by breaking longer data streams into smaller and locally stationary components.
Daniell method for power spectral density estimation in atomic force microscopy.
Labuda, Aleksander
2016-03-01
An alternative method for power spectral density (PSD) estimation--the Daniell method--is revisited and compared to the most prevalent method used in the field of atomic force microscopy for quantifying cantilever thermal motion--the Bartlett method. Both methods are shown to underestimate the Q factor of a simple harmonic oscillator (SHO) by a predictable, and therefore correctable, amount in the absence of spurious deterministic noise sources. However, the Bartlett method is much more prone to spectral leakage which can obscure the thermal spectrum in the presence of deterministic noise. By the significant reduction in spectral leakage, the Daniell method leads to a more accurate representation of the true PSD and enables clear identification and rejection of deterministic noise peaks. This benefit is especially valuable for the development of automated PSD fitting algorithms for robust and accurate estimation of SHO parameters from a thermal spectrum. PMID:27036781
Directory of Open Access Journals (Sweden)
Kaihan Fakhar
Full Text Available OBJECTIVE: We aimed in this investigation to study deep brain stimulation (DBS battery drain with special attention directed toward patient symptoms prior to and following battery replacement. BACKGROUND: Previously our group developed web-based calculators and smart phone applications to estimate DBS battery life (http://mdc.mbi.ufl.edu/surgery/dbs-battery-estimator. METHODS: A cohort of 320 patients undergoing DBS battery replacement from 2002-2012 were included in an IRB approved study. Statistical analysis was performed using SPSS 20.0 (IBM, Armonk, NY. RESULTS: The mean charge density for treatment of Parkinson's disease was 7.2 µC/cm(2/phase (SD = 3.82, for dystonia was 17.5 µC/cm(2/phase (SD = 8.53, for essential tremor was 8.3 µC/cm(2/phase (SD = 4.85, and for OCD was 18.0 µC/cm(2/phase (SD = 4.35. There was a significant relationship between charge density and battery life (r = -.59, p<.001, as well as total power and battery life (r = -.64, p<.001. The UF estimator (r = .67, p<.001 and the Medtronic helpline (r = .74, p<.001 predictions of battery life were significantly positively associated with actual battery life. Battery status indicators on Soletra and Kinetra were poor predictors of battery life. In 38 cases, the symptoms improved following a battery change, suggesting that the neurostimulator was likely responsible for symptom worsening. For these cases, both the UF estimator and the Medtronic helpline were significantly correlated with battery life (r = .65 and r = .70, respectively, both p<.001. CONCLUSIONS: Battery estimations, charge density, total power and clinical symptoms were important factors. The observation of clinical worsening that was rescued following neurostimulator replacement reinforces the notion that changes in clinical symptoms can be associated with battery drain.
Directory of Open Access Journals (Sweden)
Nikica Šprem
2012-01-01
Full Text Available Chamois (Rupicapra rupicapra L. with the Biokovo Nature Park is one of the largest and most stable populations of chamois in Croatia. Reintroduced in year 1964, and present estimated population size is estimated at 350 to 400 individuals. Estimate of population size is very important, since the animals inhabit and are often distributed across forest habitats, it is sometimes difficult and/or very expensive. Therefore, our objective was use of sensor cameras to estimate population density and population structure of chamois on the Biokovo mountain. The study was conducted in summer 2011th year, with three sensor cameras in three different localities. The cameras have recorded a total of 1003 JPEG images. During monitoring, we recorded 164 different individuals of chamois, of which there are 119 female and 45 male specimens. Daily dynamics of arriving was the highest in two periods, morning between 06:00 and 08:00, and in the evening between 18:00 and 20:00. The results of sensor cameras can be considered valid, and are extremely technical aid for the better management and protection of animal species, because we have data on the structure of the population.
Constrained Kalman Filtering Via Density Function Truncation for Turbofan Engine Health Estimation
Simon, Dan; Simon, Donald L.
2006-01-01
Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops an analytic method of incorporating state variable inequality constraints in the Kalman filter. The resultant filter truncates the PDF (probability density function) of the Kalman filter estimate at the known constraints and then computes the constrained filter estimate as the mean of the truncated PDF. The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is demonstrated via simulation results obtained from a turbofan engine model. The turbofan engine model contains 3 state variables, 11 measurements, and 10 component health parameters. It is also shown that the truncated Kalman filter may be a more accurate way of incorporating inequality constraints than other constrained filters (e.g., the projection approach to constrained filtering).
Li, Zhijin; Carton, Ann-Katherine; Muller, Serge; Iordache, Rǎzvan; Desolneux, Agnès.
2015-03-01
In breast X-ray imaging, breast texture has been characterized by a radial noise power spectrum (NPS) that has an inverse power-law shape with exponent β. The technique to estimate the radial power-law coefficient β is typically based on averaging 2-dimensional noise power spectra (NPS), calculated from partly overlapping image regions each weighted by a suitable window function. The linear regression applied over a selected frequency range to the logarithm of the 1- dimensional NPS as a function of the logarithm of the radial frequencies, gives β. For each step in this process, several alternative techniques have been proposed. This paper investigates the effect of image region of interest (ROI) size, image data windowing and alternative ways to determine radial frequency in terms of bias, variance and root mean square error (RMSE) in the estimated β. The effects of these three factors were analytically derived and evaluated using synthetic images with known β varying from 1 to 4 to cover the range of textures encountered in 2D and 3D breast X-ray imaging. Our results indicate that the RMSE in estimated β is smallest when the ROIs are multiplied with an appropriate window function and either no radial averaging or radial averaging with small frequency bins is applied. The ROI size yielding the smallest RMSE depends on several factors and needs to be validated with numerical simulations. In clinical practice however, there might be a need to compromise in the choice of the ROI size to balance between the RMSE magnitudes inherent to the applied β estimation technique and encompass the breast texture range so as to obtain an accurate shape of the NPS. When using 2.56 cm x 2.56 cm ROI sizes, applying a 2D Hann window and no radial frequency averaging, the RMSE in the estimated β ranges from 0.04 to 0.1 for true β values equal to 1 and 4. While many subtleties in real images were not modeled to simplify the mathematics in deriving our results, this work is
International Nuclear Information System (INIS)
In order to calculate criticality parameters of nuclear fuel solution systems, number density of nuclides are needed and they are generally estimated from density equations. Most of the relations allowing the calculation of the density of aqueous solutions containing the electrolytes HNO3-UO2(NO3)2-Pu(NO3)4, usually called 'nitrate dilution laws' are strictly empirical. They are obtained from a fit of assumed polynomial expressions on experimental density data. Out of their interpolation range, such mathematical expressions show discrepancies between calculated and experimental data appearing in the high concentrations range. In this study, a physico-chemical approach based on the isopiestic mixtures rule is suggested. The behaviour followed by these mixtures was first observed in 1936 by Zdanovskii and expressed as: 'Binary solutions (i.e. one electrolyte in water) having a same water activity are mixed without variation of this water activity value'. With regards to this behaviour, a set of basic thermodynamic expressions has been pointed out by Ryazanov and Vdovenko in 1965 concerning enthalpy, entropy, volume of mixtures, activity and osmotic coefficient of the components. In particular, a very simple relation for the density is obtained from the volume mixture expression depending on only two physico-chemical variables: i) concentration of each component in the mixture and in their respectively binary solutions having the same water activity as the mixture and ii), density of each component respectively in the binary solution having the same water activity as the mixture. Therefore, the calculation needs the knowledge of binary data (water activity, density and concentration) of each component at the same temperature as the mixture. Such experimental data are largely published in the literature and are available for nitric acid and uranyl nitrate. Nevertheless, nitric acid binary data show large discrepancies between the authors and need to be revised. In the
Hong, Byung-Woo
2013-11-01
We propose a mathematical framework for simultaneously delineating the boundary of object and estimating its temporal motion in the application of lesion detection in a dynamic contrast-enhanced (DCE) breast MRI sequence where both the appearance and the shape of region of interest is assumed to change in time. A unified energy functional for a joint segmentation and registration is proposed based on the assumption that the statistical properties of dynamic intensity curves within a region of interest are homogeneous. Our algorithm is designed to provide the morphological properties of the enhanced region and its dynamic intensity profiles, called kinetic signatures, in the analysis of DCE imagery since these features are considered as significant cues in understanding images. The proposed energy comprises a combination of a segmentation energy and a registration energy. The segmentation energy is developed based on a convex formulation being insensitive to the initialization. The registration energy is designed to compensate motion artifacts that are usually involved in the temporal imaging procedure. The major objective of this work is to provide a mathematical framework for a joint segmentation and registration on a dynamic sequence of images, and we demonstrate the mutual benefit of the estimation of temporal deformations for the registration step and the localization of regions of interest for the segmentation step. The effectiveness of the developed algorithm has been demonstrated on a number of clinical DCE breast MRI data in the application of breast lesion detection and the results show its potential to improve the accuracy and the efficiency in the diagnosis of breast cancer.
International Nuclear Information System (INIS)
Elderly patients become more important in oncology. In this group, personalized treatment approaches taking into account survival prognoses and comorbidities play a major role. Predictive instruments are necessary to estimate the survival of elderly cancer patients. The importance of separate instruments for different tumor entities has been recognized. In this study, an instrument was generated to estimate the survival of elderly patients developing metastatic spinal cord compression (MSCC) from breast cancer. In 218 elderly patients (age ≥65 years) irradiated for MSCC from breast cancer, nine factors were evaluated for survival: fractionation regimen, age, time from breast cancer diagnosis to RT of MSCC, visceral metastases, other bone metastases, time developing motor deficits, pre-radiotherapy ambulatory status, number of involved vertebrae, and Eastern Cooperative Oncology Group (ECOG) performance score. Factors significantly associated with survival in the Cox regression analysis were included in the prognostic instrument. Scores for each factor were calculated by dividing the 6-months survival rates by 10. The sums of these scores represented the patients’ scores. On multivariate analyses, visceral metastases (p < 0.001), time developing motor deficits (p < 0.001), ambulatory status (p < 0.001), number of involved vertebrae (p = 0.032), and ECOG performance score (p < 0.001) were significant and included in the prognostic instrument. Based on the patients’ scores, three groups were designed: 18–27 points, 28–39 points and 40–42 points. Six-months survival rates were 4, 62 and 100 %, respectively (p < 0.001). This new instrument contributes to personalized treatment in elderly patients with MSCC from breast cancer by predicting an individual patient’s survival prognosis
International Nuclear Information System (INIS)
Mammographic density (MD) and malignant-appearing microcalcifications (MAMCs) represent the earliest mammographic findings of non-palpable breast carcinomas. Matrix proteoglycans versican and decorin are frequently over-expressed in various malignancies and are differently involved in the progression of cancer. In the present study, we have evaluated the expression of versican and decorin in non-palpable breast carcinomas and their association with high risk mammographic findings and tumor characteristics. Three hundred and ten patients with non-palpable suspicious breast lesions, detected during screening mammography, were studied. Histological examination was carried out and the expression of decorin, versican, estrogen receptor α (ERα), progesterone receptor (PR) and c-erbB2 (HER-2/neu) was assessed by immunohistochemistry. Histological examination showed 83 out of 310 (26.8%) carcinomas of various subtypes. Immunohistochemistry was carried out in 62/83 carcinomas. Decorin was accumulated in breast tissues with MD and MAMCs independently of the presence of malignancy. In contrast, versican was significantly increased only in carcinomas with MAMCs (median ± SE: 42.0 ± 9.1) and MD (22.5 ± 10.1) as compared to normal breast tissue with MAMCs (14.0 ± 5.8), MD (11.0 ± 4.4) and normal breast tissue without mammographic findings (10.0 ± 2.0). Elevated levels of versican were correlated with higher tumor grade and invasiveness in carcinomas with MD and MAMCs, whereas increased amounts of decorin were associated with in situ carcinomas in MAMCs. Stromal deposition of both proteoglycans was related to higher expression of ERα and PR in tumor cells only in MAMCs. The specific accumulation of versican in breast tissue with high MD and MAMCs only in the presence of malignant transformation and its association with the aggressiveness of the tumor suggests its possible use as molecular marker in non-palpable breast carcinomas
Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus.
Campos, Zilca; Magnusson, William E
2016-01-01
Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians. PMID:27224473
Density and Biomass Estimates by Removal for an Amazonian Crocodilian, Paleosuchus palpebrosus.
Directory of Open Access Journals (Sweden)
Zilca Campos
Full Text Available Direct counts of crocodilians are rarely feasible and it is difficult to meet the assumptions of mark-recapture methods for most species in most habitats. Catch-out experiments are also usually not logistically or morally justifiable because it would be necessary to destroy the habitat in order to be confident that most individuals had been captured. We took advantage of the draining and filling of a large area of flooded forest during the building of the Santo Antônio dam on the Madeira River to obtain accurate estimates of the density and biomass of Paleosuchus palpebrosus. The density, 28.4 non-hatchling individuals per km2, is one of the highest reported for any crocodilian, except for species that are temporarily concentrated in small areas during dry-season drought. The biomass estimate of 63.15 kg*km-2 is higher than that for most or even all mammalian carnivores in tropical forest. P. palpebrosus may be one of the World´s most abundant crocodilians.
The Wegner Estimate and the Integrated Density of States for some Random Operators
Indian Academy of Sciences (India)
J M Combes; P D Hislop; Frédéric Klopp; Shu Nakamura
2002-02-01
The integrated density of states (IDS) for random operators is an important function describing many physical characteristics of a random system. Properties of the IDS are derived from the Wegner estimate that describes the influence of finite-volume perturbations on a background system. In this paper, we present a simple proof of the Wegner estimate applicable to a wide variety of random perturbations of deterministic background operators. The proof yields the correct volume dependence of the upper bound. This implies the local Hölder continuity of the integrated density of states at energies in the unperturbed spectral gap. The proof depends on the -theory of the spectral shift function (SSF), for ≥ 1, applicable to pairs of self-adjoint operators whose difference is in the trace ideal $\\mathcal{I}_p$, for 0 < ≤ 1. We present this and other results on the SSF due to other authors. Under an additional condition of the single-site potential, local Hölder continuity is proved at all energies. Finally, we present extensions of this work to random potentials with nonsign definite single-site potentials.
Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction
Directory of Open Access Journals (Sweden)
Mottaz Anaïs
2008-04-01
Full Text Available Abstract Background This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions as defined in ENTREZ-Gene based on a MEDLINE record. Inputs for this task include both a gene and a pointer to a MEDLINE reference. In the suggested approach we merge two independent sentence extraction strategies. The first proposed strategy (LASt uses argumentative features, inspired by discourse-analysis models. The second extraction scheme (GOEx uses an automatic text categorizer to estimate the density of Gene Ontology categories in every sentence; thus providing a full ranking of all possible candidate GeneRiFs. A combination of the two approaches is proposed, which also aims at reducing the size of the selected segment by filtering out non-content bearing rhetorical phrases. Results Based on the TREC-2003 Genomics collection for GeneRiF identification, the LASt extraction strategy is already competitive (52.78%. When used in a combined approach, the extraction task clearly shows improvement, achieving a Dice score of over 57% (+10%. Conclusions Argumentative representation levels and conceptual density estimation using Gene Ontology contents appear complementary for functional annotation in proteomics.
Power spectral density of velocity fluctuations estimated from phase Doppler data
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Jicha Miroslav
2012-04-01
Full Text Available Laser Doppler Anemometry (LDA and its modifications such as PhaseDoppler Particle Anemometry (P/DPA is point-wise method for optical nonintrusive measurement of particle velocity with high data rate. Conversion of the LDA velocity data from temporal to frequency domain – calculation of power spectral density (PSD of velocity fluctuations, is a non trivial task due to nonequidistant data sampling in time. We briefly discuss possibilities for the PSD estimation and specify limitations caused by seeding density and other factors of the flow and LDA setup. Arbitrary results of LDA measurements are compared with corresponding Hot Wire Anemometry (HWA data in the frequency domain. Slot correlation (SC method implemented in software program Kern by Nobach (2006 is used for the PSD estimation. Influence of several input parameters on resulting PSDs is described. Optimum setup of the software for our data of particle-laden air flow in realistic human airway model is documented. Typical character of the flow is described using PSD plots of velocity fluctuations with comments on specific properties of the flow. Some recommendations for improvements of future experiments to acquire better PSD results are given.
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Alexej P. K. Sirén
2016-01-01
Full Text Available Camera-traps are increasingly used to estimate wildlife abundance, yet few studies exist for small-sized carnivores or comparing efficacy against traditional methods. We developed a camera-trap to identify the unique ventral patches of American martens (Martes americana. Our method was designed to: (1 determine the optimal trap configuration to photograph ventral patches; (2 evaluate the use of temporally clustered photographs to determine independence and improve identification; and (3 determine factors that influence identification probability. We tested our method by comparing camera- and live-trap density estimates using spatial capture–recapture (SCR models. The ventral patches of radio-collared martens were most visible when traps were placed 15–20 cm above a feeding platform. Radio-collared martens (n = 14 visited camera-traps for long periods (median = 7 min with long intervals between visits (median = 419 min, and visits by different martens at the same trap <15 min apart was infrequent (n = 3 during both years. Similarly, there was complete agreement among observers that clustered photos of un-collared martens were always of the same individual. Pairwise agreement was high between observers; eight un-collared martens were identifiable by consensus on 90% (54 of 60 of recorded visits. Factors influencing identification probability were directly related to the time martens spent feeding at traps (β = 0.143, P = 0.01 and inversely proportional to the time that elapsed since traps were baited (β = −0.344, P = 0.006. Density estimates were higher and more precise for camera-trapping (0.60, 0.35–1.01 martens/km2 than live-trapping (0.45, 0.16–1.22 martens/km2, providing evidence that SCR density estimates may be biased when capture heterogeneity is present, yet cannot be accounted for due to small sample size. Our camera-trap method provides a minimally invasive and accurate tool for monitoring marten populations.
Estimation of Engine Intake Air Mass Flow using a generic Speed-Density method
Directory of Open Access Journals (Sweden)
Vojtíšek Michal
2014-10-01
Full Text Available Measurement of real driving emissions (RDE from internal combustion engines under real-world operation using portable, onboard monitoring systems (PEMS is becoming an increasingly important tool aiding the assessment of the effects of new fuels and technologies on environment and human health. The knowledge of exhaust flow is one of the prerequisites for successful RDE measurement with PEMS. One of the simplest approaches for estimating the exhaust flow from virtually any engine is its computation from the intake air flow, which is calculated from measured engine rpm and intake manifold charge pressure and temperature using a generic speed-density algorithm, applicable to most contemporary four-cycle engines. In this work, a generic speed-density algorithm was compared against several reference methods on representative European production engines - a gasoline port-injected automobile engine, two turbocharged diesel automobile engines, and a heavy-duty turbocharged diesel engine. The overall results suggest that the uncertainty of the generic speed-density method is on the order of 10% throughout most of the engine operating range, but increasing to tens of percent where high-volume exhaust gas recirculation is used. For non-EGR engines, such uncertainty is acceptable for many simpler and screening measurements, and may be, where desired, reduced by engine-specific calibration.
PDE-Foam-A probability density estimation method using self-adapting phase-space binning
International Nuclear Information System (INIS)
Probability density estimation (PDE) is a multi-variate discrimination technique based on sampling signal and background densities defined by event samples from data or Monte-Carlo (MC) simulations in a multi-dimensional phase space. In this paper, we present a modification of the PDE method that uses a self-adapting binning method to divide the multi-dimensional phase space in a finite number of hyper-rectangles (cells). The binning algorithm adjusts the size and position of a predefined number of cells inside the multi-dimensional phase space, minimising the variance of the signal and background densities inside the cells. The implementation of the binning algorithm (PDE-Foam) is based on the MC event-generation package Foam. We present performance results for representative examples (toy models) and discuss the dependence of the obtained results on the choice of parameters. The new PDE-Foam shows improved classification capability for small training samples and reduced classification time compared to the original PDE method based on range searching.
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Shanshan Yang
Full Text Available Detection of dysphonia is useful for monitoring the progression of phonatory impairment for patients with Parkinson's disease (PD, and also helps assess the disease severity. This paper describes the statistical pattern analysis methods to study different vocal measurements of sustained phonations. The feature dimension reduction procedure was implemented by using the sequential forward selection (SFS and kernel principal component analysis (KPCA methods. Four selected vocal measures were projected by the KPCA onto the bivariate feature space, in which the class-conditional feature densities can be approximated with the nonparametric kernel density estimation technique. In the vocal pattern classification experiments, Fisher's linear discriminant analysis (FLDA was applied to perform the linear classification of voice records for healthy control subjects and PD patients, and the maximum a posteriori (MAP decision rule and support vector machine (SVM with radial basis function kernels were employed for the nonlinear classification tasks. Based on the KPCA-mapped feature densities, the MAP classifier successfully distinguished 91.8% voice records, with a sensitivity rate of 0.986, a specificity rate of 0.708, and an area value of 0.94 under the receiver operating characteristic (ROC curve. The diagnostic performance provided by the MAP classifier was superior to those of the FLDA and SVM classifiers. In addition, the classification results indicated that gender is insensitive to dysphonia detection, and the sustained phonations of PD patients with minimal functional disability are more difficult to be correctly identified.
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Lingling Jiang
2016-01-01
Full Text Available A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N dependent parameterizations of the spectral backscattering coefficients, bb(λ, obtained from in situ measurements. There was a strong relationship between bb(λ and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to the field measurements of the coastal waters (the average relative error was only 8.9%, but it could not accurately discern the red tide from mixed pixels, and this led to overestimation of the area affected by the red tide. While the single-band inversion model is less precise than the former model in the high chlorophyll water, it could eliminate the impact of the suspended sediments and make more accurate estimates of the red tide area. We concluded that the two models both have advantages and disadvantages; these methods lay the foundation for developing a remote sensing forecasting system for red tides.
Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong
2016-05-30
Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data. PMID:27410085
Ekpo, Ernest U; Brennan, Patrick C; Mello-Thoms, Claudia; McEntee, Mark F
2016-06-01
Background Lower breast density (BD) is associated with lower risk of breast cancer and may serve as a biomarker for the efficacy of chemopreventive strategies. This review explores parameters that are thought to be associated with lower BD. We conducted a systematic review of articles published to date using the PRISMA strategy. Articles that assessed change in BD with estrogen-receptor modulators (tamoxifene [TAM], raloxifene [RLX], and tibolone) and aromatase inhibitors (AIs), as well as cross-sectional and longitudinal studies (LSs) that assessed association between BD and physical activity (PA) or diet were reviewed. Results Ten studies assessed change in BD with TAM; all reported TAM-mediated BD decreases. Change in BD with RLX was assessed by 11 studies; 3 reported a reduction in BD. Effect of tibolone was assessed by 5 RCTs; only 1 reported change in BD. AI-mediated BD reduction was reported by 3 out of 10 studies. The association between PA and BD was assessed by 21 studies; 4 reported an inverse association. The relationship between diet and BD was assessed in 34 studies. All studies on calcium and vitamin D as well as vegetable intake reported an inverse association with BD in premenopausal women. Two RCTs demonstrated BD reduction with a low-fat, high-carbohydrate intervention. Conclusion TAM induces BD reduction; however, the effect of RLX, tibolone, and AIs on BD is unclear. Although data on association between diet and BD in adulthood are contradictory, intake of vegetables, vitamin D, and calcium appear to be associated with lower BD in premenopausal women. PMID:27130722
How does spatial study design influence density estimates from spatial capture-recapture models?
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Rahel Sollmann
Full Text Available When estimating population density from data collected on non-invasive detector arrays, recently developed spatial capture-recapture (SCR models present an advance over non-spatial models by accounting for individual movement. While these models should be more robust to changes in trapping designs, they have not been well tested. Here we investigate how the spatial arrangement and size of the trapping array influence parameter estimates for SCR models. We analysed black bear data collected with 123 hair snares with an SCR model accounting for differences in detection and movement between sexes and across the trapping occasions. To see how the size of the trap array and trap dispersion influence parameter estimates, we repeated analysis for data from subsets of traps: 50% chosen at random, 50% in the centre of the array and 20% in the South of the array. Additionally, we simulated and analysed data under a suite of trap designs and home range sizes. In the black bear study, we found that results were similar across trap arrays, except when only 20% of the array was used. Black bear density was approximately 10 individuals per 100 km(2. Our simulation study showed that SCR models performed well as long as the extent of the trap array was similar to or larger than the extent of individual movement during the study period, and movement was at least half the distance between traps. SCR models performed well across a range of spatial trap setups and animal movements. Contrary to non-spatial capture-recapture models, they do not require the trapping grid to cover an area several times the average home range of the studied species. This renders SCR models more appropriate for the study of wide-ranging mammals and more flexible to design studies targeting multiple species.
A Bayesian Hierarchical Model for Estimation of Abundance and Spatial Density of Aedes aegypti.
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Daniel A M Villela
Full Text Available Strategies to minimize dengue transmission commonly rely on vector control, which aims to maintain Ae. aegypti density below a theoretical threshold. Mosquito abundance is traditionally estimated from mark-release-recapture (MRR experiments, which lack proper analysis regarding accurate vector spatial distribution and population density. Recently proposed strategies to control vector-borne diseases involve replacing the susceptible wild population by genetically modified individuals' refractory to the infection by the pathogen. Accurate measurements of mosquito abundance in time and space are required to optimize the success of such interventions. In this paper, we present a hierarchical probabilistic model for the estimation of population abundance and spatial distribution from typical mosquito MRR experiments, with direct application to the planning of these new control strategies. We perform a Bayesian analysis using the model and data from two MRR experiments performed in a neighborhood of Rio de Janeiro, Brazil, during both low- and high-dengue transmission seasons. The hierarchical model indicates that mosquito spatial distribution is clustered during the winter (0.99 mosquitoes/premise 95% CI: 0.80-1.23 and more homogeneous during the high abundance period (5.2 mosquitoes/premise 95% CI: 4.3-5.9. The hierarchical model also performed better than the commonly used Fisher-Ford's method, when using simulated data. The proposed model provides a formal treatment of the sources of uncertainty associated with the estimation of mosquito abundance imposed by the sampling design. Our approach is useful in strategies such as population suppression or the displacement of wild vector populations by refractory Wolbachia-infected mosquitoes, since the invasion dynamics have been shown to follow threshold conditions dictated by mosquito abundance. The presence of spatially distributed abundance hotspots is also formally addressed under this modeling
Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data
Dorazio, Robert M.
2013-01-01
In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.
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Purpose: We previously demonstrated that cholesterol-lowering agents regulate radiation sensitivity of inflammatory breast cancer (IBC) cell lines in vitro and are associated with less radiation resistance among IBC patients who undergo postmastectomy radiation. We hypothesized that decreasing IBC cellular cholesterol induced by treatment with lipoproteins would increase radiation sensitivity. Here, we examined the impact of specific transporters of cholesterol (ie lipoproteins) on the responses of IBC cells to self-renewal and to radiation in vitro and on clinical outcomes in IBC patients. Methods and Materials: Two patient-derived IBC cell lines, SUM 149 and KPL4, were incubated with low-density lipoproteins (LDL), very-low-density lipoproteins (VLDL), or high-density lipoproteins (HDL) for 24 hours prior to irradiation (0-6 Gy) and mammosphere formation assay. Cholesterol panels were examined in a cohort of patients with primary IBC diagnosed between 1995 and 2011 at MD Anderson Cancer Center. Lipoprotein levels were then correlated to patient outcome, using the log rank statistical model, and examined in multivariate analysis using Cox regression. Results: VLDL increased and HDL decreased mammosphere formation compared to untreated SUM 149 and KPL4 cells. Survival curves showed enhancement of survival in both of the IBC cell lines when pretreated with VLDL and, conversely, radiation sensitization in all cell lines when pretreated with HDL. In IBC patients, higher VLDL values (>30 mg/dL) predicted a lower 5-year overall survival rate than normal values (hazard ratio [HR] = 1.9 [95% confidence interval [CI]: 1.05-3.45], P=.035). Lower-than-normal patient HDL values (<60 mg/dL) predicted a lower 5-year overall survival rate than values higher than 60 mg/dL (HR = 3.21 [95% CI: 1.25-8.27], P=.015). Conclusions: This study discovered a relationship among the plasma levels of lipoproteins, overall patient response, and radiation resistance in IBC patients
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Wolfe, Adam R. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Atkinson, Rachel L. [Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Reddy, Jay P. [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Debeb, Bisrat G.; Larson, Richard; Li, Li [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Masuda, Hiroko; Brewer, Takae [Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Atkinson, Bradley J. [Department of Clinical Pharmacy Services, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Brewster, Abeena [Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Ueno, Naoto T. [Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Woodward, Wendy A., E-mail: wwoodward@mdanderson.org [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)
2015-04-01
Purpose: We previously demonstrated that cholesterol-lowering agents regulate radiation sensitivity of inflammatory breast cancer (IBC) cell lines in vitro and are associated with less radiation resistance among IBC patients who undergo postmastectomy radiation. We hypothesized that decreasing IBC cellular cholesterol induced by treatment with lipoproteins would increase radiation sensitivity. Here, we examined the impact of specific transporters of cholesterol (ie lipoproteins) on the responses of IBC cells to self-renewal and to radiation in vitro and on clinical outcomes in IBC patients. Methods and Materials: Two patient-derived IBC cell lines, SUM 149 and KPL4, were incubated with low-density lipoproteins (LDL), very-low-density lipoproteins (VLDL), or high-density lipoproteins (HDL) for 24 hours prior to irradiation (0-6 Gy) and mammosphere formation assay. Cholesterol panels were examined in a cohort of patients with primary IBC diagnosed between 1995 and 2011 at MD Anderson Cancer Center. Lipoprotein levels were then correlated to patient outcome, using the log rank statistical model, and examined in multivariate analysis using Cox regression. Results: VLDL increased and HDL decreased mammosphere formation compared to untreated SUM 149 and KPL4 cells. Survival curves showed enhancement of survival in both of the IBC cell lines when pretreated with VLDL and, conversely, radiation sensitization in all cell lines when pretreated with HDL. In IBC patients, higher VLDL values (>30 mg/dL) predicted a lower 5-year overall survival rate than normal values (hazard ratio [HR] = 1.9 [95% confidence interval [CI]: 1.05-3.45], P=.035). Lower-than-normal patient HDL values (<60 mg/dL) predicted a lower 5-year overall survival rate than values higher than 60 mg/dL (HR = 3.21 [95% CI: 1.25-8.27], P=.015). Conclusions: This study discovered a relationship among the plasma levels of lipoproteins, overall patient response, and radiation resistance in IBC patients
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Noritaka Shimizu
2016-02-01
Full Text Available We introduce a novel method to obtain level densities in large-scale shell-model calculations. Our method is a stochastic estimation of eigenvalue count based on a shifted Krylov-subspace method, which enables us to obtain level densities of huge Hamiltonian matrices. This framework leads to a successful description of both low-lying spectroscopy and the experimentally observed equilibration of Jπ=2+ and 2− states in 58Ni in a unified manner.
Akune, Tadahiro; Sakamoto, Nobuyoshi
2009-03-01
In a multifilamentary wire proximity-currents between filaments show a close resemblance with the inter-grain current in a high-Tc superconductor. The critical current densities of the proximity-induced superconducting matrix Jcm can be estimated from measured twist-pitch dependence of magnetization and have been shown to follow the well-known scaling law of the pinning strength. The grained Bean model is applied on the multifilamentary wire to obtain Jcm, where the filaments are immersed in the proximity-induced superconducting matrix. Difference of the superconducting characteristics of the filament, the matrix and the filament content factor give a variety of deformation on the AC susceptibility curves. The computed AC susceptibility curves of multifilamentary wires using the grained Bean model are favorably compared with the experimental results. The values of Jcm estimated from the susceptibilities using the grained Bean model are comparable to those estimated from measured twist-pitch dependence of magnetization. The applicability of the grained Bean model on the multifilamentary wire is discussed in detail.
Garde, Ainara; Karlen, Walter; Ansermino, J Mark; Dumont, Guy A
2014-01-01
The photoplethysmogram (PPG) obtained from pulse oximetry measures local variations of blood volume in tissues, reflecting the peripheral pulse modulated by heart activity, respiration and other physiological effects. We propose an algorithm based on the correntropy spectral density (CSD) as a novel way to estimate respiratory rate (RR) and heart rate (HR) from the PPG. Time-varying CSD, a technique particularly well-suited for modulated signal patterns, is applied to the PPG. The respiratory and cardiac frequency peaks detected at extended respiratory (8 to 60 breaths/min) and cardiac (30 to 180 beats/min) frequency bands provide RR and HR estimations. The CSD-based algorithm was tested against the Capnobase benchmark dataset, a dataset from 42 subjects containing PPG and capnometric signals and expert labeled reference RR and HR. The RR and HR estimation accuracy was assessed using the unnormalized root mean square (RMS) error. We investigated two window sizes (60 and 120 s) on the Capnobase calibration dataset to explore the time resolution of the CSD-based algorithm. A longer window decreases the RR error, for 120-s windows, the median RMS error (quartiles) obtained for RR was 0.95 (0.27, 6.20) breaths/min and for HR was 0.76 (0.34, 1.45) beats/min. Our experiments show that in addition to a high degree of accuracy and robustness, the CSD facilitates simultaneous and efficient estimation of RR and HR. Providing RR every minute, expands the functionality of pulse oximeters and provides additional diagnostic power to this non-invasive monitoring tool. PMID:24466088
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Ainara Garde
Full Text Available The photoplethysmogram (PPG obtained from pulse oximetry measures local variations of blood volume in tissues, reflecting the peripheral pulse modulated by heart activity, respiration and other physiological effects. We propose an algorithm based on the correntropy spectral density (CSD as a novel way to estimate respiratory rate (RR and heart rate (HR from the PPG. Time-varying CSD, a technique particularly well-suited for modulated signal patterns, is applied to the PPG. The respiratory and cardiac frequency peaks detected at extended respiratory (8 to 60 breaths/min and cardiac (30 to 180 beats/min frequency bands provide RR and HR estimations. The CSD-based algorithm was tested against the Capnobase benchmark dataset, a dataset from 42 subjects containing PPG and capnometric signals and expert labeled reference RR and HR. The RR and HR estimation accuracy was assessed using the unnormalized root mean square (RMS error. We investigated two window sizes (60 and 120 s on the Capnobase calibration dataset to explore the time resolution of the CSD-based algorithm. A longer window decreases the RR error, for 120-s windows, the median RMS error (quartiles obtained for RR was 0.95 (0.27, 6.20 breaths/min and for HR was 0.76 (0.34, 1.45 beats/min. Our experiments show that in addition to a high degree of accuracy and robustness, the CSD facilitates simultaneous and efficient estimation of RR and HR. Providing RR every minute, expands the functionality of pulse oximeters and provides additional diagnostic power to this non-invasive monitoring tool.
Lee, Jae-Ok; Moon, Y.-J.; Lee, Jin-Yi; Lee, Kyoung-Sun; Kim, R.-S.
2016-04-01
We determine coronal electron density distributions (CEDDs) by analyzing decahectometric (DH) type II observations under two assumptions. DH type II bursts are generated by either (1) shocks at the leading edges of coronal mass ejections (CMEs) or (2) CME shock-streamer interactions. Among 399 Wind/WAVES type II bursts (from 1997 to 2012) associated with SOHO/LASCO (Large Angle Spectroscopic COronagraph) CMEs, we select 11 limb events whose fundamental and second harmonic emission lanes are well identified. We determine the lowest frequencies of fundamental emission lanes and the heights of leading edges of their associated CMEs. We also determine the heights of CME shock-streamer interaction regions. The CEDDs are estimated by minimizing the root-mean-square error between the heights from the CME leading edges (or CME shock-streamer interaction regions) and DH type II bursts. We also estimate CEDDs of seven events using polarized brightness (pB) measurements. We find the following results. Under the first assumption, the average of estimated CEDDs from 3 to 20 Rs is about 5-fold Saito's model (NSaito(r)). Under the second assumption, the average of estimated CEDDs from 3 to 10 Rs is 1.5-fold NSaito(r). While the CEDDs obtained from pB measurements are significantly smaller than those based on the first assumption and CME flank regions without streamers, they are well consistent with those on the second assumption. Our results show that not only about 1-fold NSaito(r) is a proper CEDD for analyzing DH type II bursts but also CME shock-streamer interactions could be a plausible origin for generating DH type II bursts.
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He,P.; Blaskiewicz, M.; Fischer, W.
2009-01-02
In this report we summarize electron-cloud simulations for the RHIC dipole regions at injection and transition to estimate if scrubbing over practical time scales at injection would reduce the electron cloud density at transition to significantly lower values. The lower electron cloud density at transition will allow for an increase in the ion intensity.
Bone Density, Turnover, and Estimated Strength in Postmenopausal Women Treated With Odanacatib
DEFF Research Database (Denmark)
Brixen, Kim; Chapurlat, Roland; Cheung, Angela M;
2013-01-01
Context:Odanacatib, a cathepsin K inhibitor, increases spine and hip areal bone mineral density (BMD) in postmenopausal women with low BMD and cortical thickness in ovariectomized monkeys.Objective:The objective of the study was to examine the impact of odanacatib on the trabecular and cortical...... included odanacatib 50 mg or placebo weekly.Main Outcome Measures:Changes in areal BMD by dual-energy x-ray absorptiometry (primary end point, 1 year areal BMD change at lumbar spine), bone turnover markers, volumetric BMD by quantitative computed tomography (QCT), and bone strength estimated by finite...... element analysis were measured.Results:Year 1 lumbar spine areal BMD percent change from baseline was 3.5% greater with odanacatib than placebo (P <.001). Bone-resorption marker C-telopeptide of type 1 collagen was significantly lower with odanacatib vs placebo at 6 months and 2 years (P <.001). Bone...
International Nuclear Information System (INIS)
The patient dose from in vivo measurement of bone mass and density was estimated by a phantom method. The measurement methods studied were microdensitometry (MD method), single photon absorptiometry (SPA), dual energy X ray absorptiometry (DEXA), quantitative computed tomography (QCT) and conventional X-ray photography (X-P) for vertebrae, all of which have been used for mass screening or clinical examination of osteoporosis. The organ absorbed doses from the QCT and X ray photography were several mSv and these values were one to two orders of magnitude higher than those from the DEXA method. The effective dose and entrance skin dose from the QCT and X ray photography were one to two orders of magnitude higher than the DEXA, which were μSv and some ten μSv, respectively. The application of X-P and QCT for a young population should be carefully judged. (author)
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José Fajardo
2012-12-01
Full Text Available This paper uses the Liu et al. (2007 approach to estimate the optionimplied Risk-Neutral Densities (RND, real-world density (RWD, and relative risk aversion from the Brazilian Real/US Dollar exchange rate distribution. Our empirical application uses a sample of exchange-traded Brazilian Real currency options from 1999 to 2011. Our estimated value of the relative risk aversion is around 2.7, which is in line with other articles for the Brazilian Economy. Our out-of-sample results showed that the RND has some ability to forecast the Brazilian Real exchange rate, but when we incorporate the risk aversion, the out-of-sample performance improves substantially.Este artigo usa a abordagem de Liu et al. (2007 para estimar a densidade neutra ao risco, densidade do mundo real e a aversão relativa ao risco da distribuição da taxa de câmbio Dólar/Real. Na estimação foi utilizada uma amostra de opções Dólar/Real negociadas embolsa entre 1999 e 2011. O valor estimado para a aversão relativa ao risco foi de 2,7, em linha com outros artigos que também estimaram este parâmetro para a economia brasileira. A avaliação fora da amostra mostrou que a densidade neutra ao risco possui alguma habilidade para prever a taxa de câmbio Dólar/Real, mas quando o parâmetro de aversão ao risco é incorporado, a performance fora da amostra melhora substancialmente.
Evaluation of a brushing machine for estimating density of spider mites on grape leaves.
Macmillan, Craig D; Costello, Michael J
2015-12-01
Direct visual inspection and enumeration for estimating field population density of economically important arthropods, such as spider mites, provide more information than alternative methods, such as binomial sampling, but is laborious and time consuming. A brushing machine can reduce sampling time and perhaps improve accuracy. Although brushing technology has been investigated and recommended as a useful tool for researchers and integrated pest management practitioners, little work to demonstrate the validity of this technique has been performed since the 1950's. We investigated the brushing machine manufactured by Leedom Enterprises (Mi-Wuk Village, CA, USA) for studies on spider mites. We evaluated (1) the mite recovery efficiency relative to the number of passes of a leaf through the brushes, (2) mite counts as generated by the machine compared to visual counts under a microscope, (3) the lateral distribution of mites on the collection plate and (4) the accuracy and precision of a 10% sub-sample using a double-transect counting grid. We found that about 95% of mites on a leaf were recovered after five passes, and 99% after nine passes, and mite counts from brushing were consistently higher than those from visual inspection. Lateral distribution of mites was not uniform, being highest in concentration at the center and lowest at the periphery. The 10% double-transect pattern did not result in a significant correlation with the total plate count at low mite density, but accuracy and precision improved at medium and high density. We suggest that a more accurate and precise sample may be achieved using a modified pattern which concentrates on the center plus some of the adjacent area. PMID:26459377
Probability density function and estimation for error of digitized map coordinates in GIS
Institute of Scientific and Technical Information of China (English)
童小华; 刘大杰
2004-01-01
Traditionally, it is widely accepted that measurement error usually obeys the normal distribution. However, in this paper a new idea is proposed that the error in digitized data which is a major derived data source in GIS does not obey the normal distribution but the p-norm distribution with a determinate parameter. Assuming that the error is random and has the same statistical properties, the probability density function of the normal distribution,Laplace distribution and p-norm distribution are derived based on the arithmetic mean axiom, median axiom and pmedian axiom, which means that the normal distribution is only one of these distributions but not the least one.Based on this idea, distribution fitness tests such as Skewness and Kurtosis coefficient test, Pearson chi-square x2 test and Kolmogorov test for digitized data are conducted. The results show that the error in map digitization obeys the p-norm distribution whose parameter is close to 1.60. A least p-norm estimation and the least square estimation of digitized data are further analyzed, showing that the least p-norm adiustment is better than the least square adjustment for digitized data processing in GIS.
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A new Monte Carlo mesh tally based on a Kernel Density Estimator (KDE) approach using integrated particle tracks is presented. We first derive the KDE integral-track estimator and present a brief overview of its implementation as an alternative to the MCNP fmesh tally. To facilitate a valid quantitative comparison between these two tallies for verification purposes, there are two key issues that must be addressed. The first of these issues involves selecting a good data transfer method to convert the nodal-based KDE results into their cell-averaged equivalents (or vice versa with the cell-averaged MCNP results). The second involves choosing an appropriate resolution of the mesh, since if it is too coarse this can introduce significant errors into the reference MCNP solution. After discussing both of these issues in some detail, we present the results of a convergence analysis that shows the KDE integral-track and MCNP fmesh tallies are indeed capable of producing equivalent results for some simple 3D transport problems. In all cases considered, there was clear convergence from the KDE results to the reference MCNP results as the number of particle histories was increased. (authors)
Institute of Scientific and Technical Information of China (English)
YAN Hao; WANG Hu; WANG Yong-hui; ZHANG Yu-mei
2013-01-01
Background The classification of Alzheimer's disease (AD) from magnetic resonance imaging (MRI) has been challenged by lack of effective and reliable biomarkers due to inter-subject variability.This article presents a classification method for AD based on kernel density estimation (KDE) of local features.Methods First,a large number of local features were extracted from stable image blobs to represent various anatomical patterns for potential effective biomarkers.Based on distinctive descriptors and locations,the local features were robustly clustered to identify correspondences of the same underlying patterns.Then,the KDE was used to estimate distribution parameters of the correspondences by weighting contributions according to their distances.Thus,biomarkers could be reliably quantified by reducing the effects of further away correspondences which were more likely noises from inter-subject variability.Finally,the Bayes classifier was applied on the distribution parameters for the classification of AD.Results Experiments were performed on different divisions of a publicly available database to investigate the accuracy and the effects of age and AD severity.Our method achieved an equal error classification rate of 0.85 for subject aged 60-80 years exhibiting mild AD and outperformed a recent local feature-based work regardless of both effects.Conclusions We proposed a volumetric brain MRI classification method for neurodegenerative disease based on statistics of local features using KDE.The method may be potentially useful for the computer-aided diagnosis in clinical settings.
NEAR INFRARED SPECTROSCOPY FOR ESTIMATING SUGARCANE BAGASSE CONTENT IN MEDIUM DENSITY FIBERBOARD
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Ugo Leandro Belini
2011-04-01
Full Text Available Medium density fiberboard (MDF is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC bagasse to Eucalyptus wood in MDF panels using near infrared (NIR spectroscopy. Principal component analysis (PCA and partial least square (PLS regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96 between the NIR-predicted and Lab-determined values and a low standard error of prediction (~1.5% in the cross-validations. A key role of resins (adhesives, cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.
Lebel, Ehud; Mishukov, Yuri; Babchenko, Liana; Samueloff, Arnon; Zimran, Ari; Elstein, Deborah
2014-01-01
Changes of bone during pregnancy and during lactation evaluated by bone mineral density (BMD) may have implications for risk of osteoporosis and fractures. We studied BMD in women of differing ages, parity, and lactation histories immediately postpartum for BMD, T-scores, and Z-scores. Institutional Review Board approval was received. All women while still in hospital postpartum were asked to participate. BMD was performed by dual-energy X-ray absorptiometry (DXA) machine at femoral neck (FN) and lumbar spine (LS) by a single technician. Of 132 participants, 73 (55.3%) were ≤30 years; 27 (20.5%) were primiparous; 36 (27.3%) were grand multiparous; 35 (26.5%) never breast fed. Mean FN T-scores and Z-scores were higher than respective mean LS scores, but all means were within the normal limits. Mean LS T-scores and Z-scores were highest in the grand multiparas. There were only 2 (1.5%) outliers with low Z-scores. We conclude that, in a large cohort of Israeli women with BMD parameters assessed by DXA within two days postpartum, mean T-scores and Z-scores at both the LS and FN were within normal limits regardless of age (20-46 years), parity (1-13 viable births), and history of either no or prolonged months of lactation (up to 11.25 years). PMID:25506038
Using kernel density estimation to understand the influence of neighbourhood destinations on BMI
King, Tania L; Bentley, Rebecca J; Thornton, Lukar E; Kavanagh, Anne M
2016-01-01
Objectives Little is known about how the distribution of destinations in the local neighbourhood is related to body mass index (BMI). Kernel density estimation (KDE) is a spatial analysis technique that accounts for the location of features relative to each other. Using KDE, this study investigated whether individuals living near destinations (shops and service facilities) that are more intensely distributed rather than dispersed, have lower BMIs. Study design and setting A cross-sectional study of 2349 residents of 50 urban areas in metropolitan Melbourne, Australia. Methods Destinations were geocoded, and kernel density estimates of destination intensity were created using kernels of 400, 800 and 1200 m. Using multilevel linear regression, the association between destination intensity (classified in quintiles Q1(least)–Q5(most)) and BMI was estimated in models that adjusted for the following confounders: age, sex, country of birth, education, dominant household occupation, household type, disability/injury and area disadvantage. Separate models included a physical activity variable. Results For kernels of 800 and 1200 m, there was an inverse relationship between BMI and more intensely distributed destinations (compared to areas with least destination intensity). Effects were significant at 1200 m: Q4, β −0.86, 95% CI −1.58 to −0.13, p=0.022; Q5, β −1.03 95% CI −1.65 to −0.41, p=0.001. Inclusion of physical activity in the models attenuated effects, although effects remained marginally significant for Q5 at 1200 m: β −0.77 95% CI −1.52, −0.02, p=0.045. Conclusions This study conducted within urban Melbourne, Australia, found that participants living in areas of greater destination intensity within 1200 m of home had lower BMIs. Effects were partly explained by physical activity. The results suggest that increasing the intensity of destination distribution could reduce BMI levels by encouraging higher levels of physical activity
Kaye, Jason; Yang, Chao
2014-01-01
Kohn-Sham density functional theory is one of the most widely used electronic structure theories. The recently developed adaptive local basis functions form an accurate and systematically improvable basis set for solving Kohn-Sham density functional theory using discontinuous Galerkin methods, requiring a small number of basis functions per atom. In this paper we develop residual-based a posteriori error estimates for the adaptive local basis approach, which can be used to guide non-uniform basis refinement for highly inhomogeneous systems such as surfaces and large molecules. The adaptive local basis functions are non-polynomial basis functions, and standard a posteriori error estimates for $hp$-refinement using polynomial basis functions do not directly apply. We generalize the error estimates for $hp$-refinement to non-polynomial basis functions. We demonstrate the practical use of the a posteriori error estimator in performing three-dimensional Kohn-Sham density functional theory calculations for quasi-2D...
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François Pimont
2015-06-01
Full Text Available Leaf biomass distribution is a key factor for modeling energy and carbon fluxes in forest canopies and for assessing fire behavior. We propose a new method to estimate 3D leaf bulk density distribution, based on a calibration of indices derived from T-LiDAR. We applied the method to four contrasted plots in a mature Quercus pubescens forest. Leaf bulk densities were measured inside 0.7 m-diameter spheres, referred to as Calibration Volumes. Indices were derived from LiDAR point clouds and calibrated over the Calibration Volume bulk densities. Several indices were proposed and tested to account for noise resulting from mixed pixels and other theoretical considerations. The best index and its calibration parameter were then used to estimate leaf bulk densities at the grid nodes of each plot. These LiDAR-derived bulk density distributions were used to estimate bulk density vertical profiles and loads and above four meters compared well with those assessed by the classical inventory-based approach. Below four meters, the LiDAR-based approach overestimated bulk densities since no distinction was made between wood and leaf returns. The results of our method are promising since they demonstrate the possibility to assess bulk density on small plots at a reasonable operational cost.
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We designed this study to quantify the effects of radiotherapy (RT) on bone density as a local response in spinal bone metastases of women with breast cancer and, secondly, to establish bone density as an accurate and reproducible marker for assessment of local response to RT in spinal bone metastases. We retrospectively assessed 135 osteolytic spinal metastases in 115 women with metastatic breast cancer treated at our department between January 2000 and January 2012. Primary endpoint was to compare bone density in the bone metastases before, 3 months after and 6 months after RT. Bone density was measured in Hounsfield units (HU) in computed tomography scans. We calculated mean values in HU and the standard deviation (SD) as a measurement of bone density before, 3 months and 6 months after RT. T-test was used for statistical analysis of difference in bone density as well as for univariate analysis of prognostic factors for difference in bone density 3 and 6 months after RT. Mean bone density was 194.8 HU ± SD 123.0 at baseline. Bone density increased significantly by a mean of 145.8 HU ± SD 139.4 after 3 months (p = .0001) and by 250.3 HU ± SD 147.1 after 6 months (p < .0001). Women receiving bisphosphonates showed a tendency towards higher increase in bone density in the metastases after 3 months (152.6 HU ± SD 141.9 vs. 76.0 HU ± SD 86.1; p = .069) and pathological fractures before RT were associated with a significantly higher increase in bone density after 3 months (202.3 HU ± SD 161.9 vs. 130.3 HU ± SD 129.2; p = .013). Concomitant chemotherapy (ChT) or endocrine therapy (ET), hormone receptor status, performance score, applied overall RT dose and prescription of a surgical corset did not correlate with a difference in bone density after RT. Bone density measurement in HU is a practicable and reproducible method for assessment of local RT response in osteolytic metastases in breast cancer. Our analysis demonstrated an excellent local response within
SU-D-204-01: Dual-Energy Calibration for Breast Density Measurement Using Spectral Mammography
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Ding, H; Cho, H; Kumar, N; Sennung, D; Molloi, S [Department of Radiological Sciences, University of California, Irvine, CA (United States)
2015-06-15
Purpose: To investigate the feasibility of minimizing the systematic errors in dual-energy breast density quantification induced by the use of tissue-equivalent plastic phantoms as the calibration basis materials. Methods: Dual-energy calibration using tissue-equivalent plastic phantoms was performed on a spectral mammography system based on scanning multi-slit Si strip photon-counting detectors. The plastic phantom calibration used plastic water and adipose-equivalent phantoms as the basis materials, which have different x-ray attenuation properties compared to water and lipid in actual breast tissue. Two methods were used to convert the dual-energy decomposition measurements in plastic phantom thicknesses into true water and lipid basis. The first method was based entirely on the theoretical x-ray attenuation coefficients of the investigated materials in the mammographic energy range. The conversion matrix was determined from least-squares fitting of the target material using the reported attenuation coefficients of water and lipid. The second method was developed based on experimental calibrations, which measured the low-and high-energy signals of pure water and lipid of known thicknesses. A non-linear rational function was used to correlate the decomposed thicknesses to the known values, so that the conversion coefficients can be determined. Both methods were validated using independent measurements of water and lipid mixture phantoms. The correlation of the dual-energy decomposition measurements and the known values were studied with linear regression analysis. Results: There was an excellent linear correlation between the converted water thicknesses and the known values. The slopes of the linear fits were determined to be 0.63 and 1.03 for the simulation and experimental results, respectively. The non-linear fitting in the experimental approach reduced the root-mean-square (RMS) errors from approximately 3.4 mm to 1.5 mm. Conclusion: The results suggested
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Marianne Sandin
2015-09-01
Full Text Available Protein translocation between organelles in the cell is an important process that regulates many cellular functions. However, organelles can rarely be isolated to purity so several methods have been developed to analyse the fractions obtained by density gradient centrifugation. We present an analysis of the distribution of proteins amongst organelles in the human breast cell line, MDA-MB-231 using two approaches: an isotopic labelling and a label-free approach.
George, Stephanie M; McTiernan, Anne; Villaseñor, Adriana; Alfano, Catherine M.; Irwin, Melinda L.; Neuhouser, Marian L.; Baumgartner, Richard N.; Baumgartner, Kathy B.; Bernstein, Leslie; Smith, Ashley W.; Ballard-Barbash, Rachel
2013-01-01
Abstract Background Bone mineral density (BMD) and lean mass (LM) may both decrease in breast cancer survivors, thereby increasing risk of falls and fractures. Research is needed to determine whether lean mass (LM) and fat mass (FM) independently relate to BMD in this patient group. Methods The Health, Eating, Activity, and Lifestyle Study participants included 599 women, ages 29–87 years, diagnosed...
Optical Density Analysis of X-Rays Utilizing Calibration Tooling to Estimate Thickness of Parts
Grau, David
2012-01-01
This process is designed to estimate the thickness change of a material through data analysis of a digitized version of an x-ray (or a digital x-ray) containing the material (with the thickness in question) and various tooling. Using this process, it is possible to estimate a material's thickness change in a region of the material or part that is thinner than the rest of the reference thickness. However, that same principle process can be used to determine the thickness change of material using a thinner region to determine thickening, or it can be used to develop contour plots of an entire part. Proper tooling must be used. An x-ray film with an S-shaped characteristic curve or a digital x-ray device with a product resulting in like characteristics is necessary. If a film exists with linear characteristics, this type of film would be ideal; however, at the time of this reporting, no such film has been known. Machined components (with known fractional thicknesses) of a like material (similar density) to that of the material to be measured are necessary. The machined components should have machined through-holes. For ease of use and better accuracy, the throughholes should be a size larger than 0.125 in. (.3 mm). Standard components for this use are known as penetrameters or image quality indicators. Also needed is standard x-ray equipment, if film is used in place of digital equipment, or x-ray digitization equipment with proven conversion properties. Typical x-ray digitization equipment is commonly used in the medical industry, and creates digital images of x-rays in DICOM format. It is recommended to scan the image in a 16-bit format. However, 12-bit and 8-bit resolutions are acceptable. Finally, x-ray analysis software that allows accurate digital image density calculations, such as Image-J freeware, is needed. The actual procedure requires the test article to be placed on the raw x-ray, ensuring the region of interest is aligned for perpendicular x-ray exposure
Wang, Ying; Wu, Fengchang; Giesy, John P; Feng, Chenglian; Liu, Yuedan; Qin, Ning; Zhao, Yujie
2015-09-01
Due to use of different parametric models for establishing species sensitivity distributions (SSDs), comparison of water quality criteria (WQC) for metals of the same group or period in the periodic table is uncertain and results can be biased. To address this inadequacy, a new probabilistic model, based on non-parametric kernel density estimation was developed and optimal bandwidths and testing methods are proposed. Zinc (Zn), cadmium (Cd), and mercury (Hg) of group IIB of the periodic table are widespread in aquatic environments, mostly at small concentrations, but can exert detrimental effects on aquatic life and human health. With these metals as target compounds, the non-parametric kernel density estimation method and several conventional parametric density estimation methods were used to derive acute WQC of metals for protection of aquatic species in China that were compared and contrasted with WQC for other jurisdictions. HC5 values for protection of different types of species were derived for three metals by use of non-parametric kernel density estimation. The newly developed probabilistic model was superior to conventional parametric density estimations for constructing SSDs and for deriving WQC for these metals. HC5 values for the three metals were inversely proportional to atomic number, which means that the heavier atoms were more potent toxicants. The proposed method provides a novel alternative approach for developing SSDs that could have wide application prospects in deriving WQC and use in assessment of risks to ecosystems. PMID:25953609
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Niels Halama
Full Text Available BACKGROUND: Determining the correct number of positive immune cells in immunohistological sections of colorectal cancer and other tumor entities is emerging as an important clinical predictor and therapy selector for an individual patient. This task is usually obstructed by cell conglomerates of various sizes. We here show that at least in colorectal cancer the inclusion of immune cell conglomerates is indispensable for estimating reliable patient cell counts. Integrating virtual microscopy and image processing principally allows the high-throughput evaluation of complete tissue slides. METHODOLOGY/PRINCIPAL FINDINGS: For such large-scale systems we demonstrate a robust quantitative image processing algorithm for the reproducible quantification of cell conglomerates on CD3 positive T cells in colorectal cancer. While isolated cells (28 to 80 microm(2 are counted directly, the number of cells contained in a conglomerate is estimated by dividing the area of the conglomerate in thin tissues sections (< or =6 microm by the median area covered by an isolated T cell which we determined as 58 microm(2. We applied our algorithm to large numbers of CD3 positive T cell conglomerates and compared the results to cell counts obtained manually by two independent observers. While especially for high cell counts, the manual counting showed a deviation of up to 400 cells/mm(2 (41% variation, algorithm-determined T cell numbers generally lay in between the manually observed cell numbers but with perfect reproducibility. CONCLUSION: In summary, we recommend our approach as an objective and robust strategy for quantifying immune cell densities in immunohistological sections which can be directly implemented into automated full slide image processing systems.
Near-native protein loop sampling using nonparametric density estimation accommodating sparcity.
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Hyun Joo
2011-10-01
Full Text Available Unlike the core structural elements of a protein like regular secondary structure, template based modeling (TBM has difficulty with loop regions due to their variability in sequence and structure as well as the sparse sampling from a limited number of homologous templates. We present a novel, knowledge-based method for loop sampling that leverages homologous torsion angle information to estimate a continuous joint backbone dihedral angle density at each loop position. The φ,ψ distributions are estimated via a Dirichlet process mixture of hidden Markov models (DPM-HMM. Models are quickly generated based on samples from these distributions and were enriched using an end-to-end distance filter. The performance of the DPM-HMM method was evaluated against a diverse test set in a leave-one-out approach. Candidates as low as 0.45 Å RMSD and with a worst case of 3.66 Å were produced. For the canonical loops like the immunoglobulin complementarity-determining regions (mean RMSD 7.0 Å, this sampling method produces a population of loop structures to around 3.66 Å for loops up to 17 residues. In a direct test of sampling to the Loopy algorithm, our method demonstrates the ability to sample nearer native structures for both the canonical CDRH1 and non-canonical CDRH3 loops. Lastly, in the realistic test conditions of the CASP9 experiment, successful application of DPM-HMM for 90 loops from 45 TBM targets shows the general applicability of our sampling method in loop modeling problem. These results demonstrate that our DPM-HMM produces an advantage by consistently sampling near native loop structure. The software used in this analysis is available for download at http://www.stat.tamu.edu/~dahl/software/cortorgles/.
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Yu Xu
2016-06-01
Full Text Available Estimates of abundance or density are essential for wildlife management and conservation. There are few effective density estimates for the Buff-throated Partridge Tetraophasis szechenyii, a rare and elusive high-mountain Galliform species endemic to western China. In this study, we used the temporary emigration N-mixture model to estimate density of this species, with data acquired from playback point count surveys around a sacred area based on indigenous Tibetan culture of protection of wildlife, in Yajiang County, Sichuan, China, during April-June 2009. Within 84 125-m radius points, we recorded 53 partridge groups during three repeats. The best model indicated that detection probability was described by covariates of vegetation cover type, week of visit, time of day, and weather with weak effects, and a partridge group was present during a sampling period with a constant probability. The abundance component was accounted for by vegetation association. Abundance was substantially higher in rhododendron shrubs, fir-larch forests, mixed spruce-larch-birch forests, and especially oak thickets than in pine forests. The model predicted a density of 5.14 groups/km², which is similar to an estimate of 4.7 - 5.3 groups/km² quantified via an intensive spot-mapping effort. The post-hoc estimate of individual density was 14.44 individuals/km², based on the estimated mean group size of 2.81. We suggest that the method we employed is applicable to estimate densities of Buff-throated Partridges in large areas. Given importance of a mosaic habitat for this species, local logging should be regulated. Despite no effect of the conservation area (sacred on the abundance of Buff-throated Partridges, we suggest regulations linking the sacred mountain conservation area with the official conservation system because of strong local participation facilitated by sacred mountains in land conservation.
Effect of sampling density and design on estimation of streambed attributes
Kennedy, Casey D.; Genereux, David P.; Mitasova, Helena; Corbett, D. Reide; Leahy, Scott
2008-06-01
effect of "diminishing returns" was evident for sampling densities greater than ∼24 points per reach (roughly 0.05-0.06 points per m2 of streambed). Relative to sampling density, sampling design had little effect on values of p. Average error in streambed attributes was generally small (⩽10%) and less than the 95% confidence limits about the reach-average values of the attributes. The ability to estimate unknown point values by interpolation among other point values was poor using both 12- and 36-point subsets, though results suggest the 24 additional known point values (in going from 12 to 36) were helpful in one case in which there was some degree of autocorrelation between the additional known values and the values to be predicted in the interpolation. Visual inspection of 130 contour maps showed that those based on 36-point values were far more realistic in appearance than those based on 12-point values (where the standard for "realistic" appearance was the contour maps based on the full datasets of 54-point values).
Institute of Scientific and Technical Information of China (English)
张凌; 常加峰; 张炜; 李颖颖; 钱金平; 徐国盛; 丁斯晔; 高伟; 吴振伟; 陈颖杰; 黄娟; 刘晓菊; 臧庆
2011-01-01
In this work, population coefficients of hydrogen＇s n = 3 excited state from the hydrogen collisional-radiative （CR） model, from the data file of DEGAS 2, are used to calculate the photon emissivity coefficients （PECs） of hydrogen Balmer-α （n = 3 →n = 2） （Hα）. The results are compared with the PECs from Atomic Data and Analysis Structure （ADAS） database, and a good agreement is found. A magnetic surface-averaged neutral density profile of typical double-null （DN） plasma in EAST is obtained by using FRANTIC, the 1.5-D fluid transport code. It is found that the sum of integral Dα and Hα emission intensity calculated via the neutral density agrees with the measured results obtained by using the absolutely calibrated multi-channel poloidal photodiode array systems viewing the lower divertor at the last closed flux surface （LCFS）. It is revealed that the typical magnetic surface-averaged neutral density at LCFS is about 3.5×10^16 m^-3 .
Jennelle, C.S.; Runge, M.C.; MacKenzie, D.I.
2002-01-01
The search for easy-to-use indices that substitute for direct estimation of animal density is a common theme in wildlife and conservation science, but one fraught with well-known perils (Nichols & Conroy, 1996; Yoccoz, Nichols & Boulinier, 2001; Pollock et al., 2002). To establish the utility of an index as a substitute for an estimate of density, one must: (1) demonstrate a functional relationship between the index and density that is invariant over the desired scope of inference; (2) calibrate the functional relationship by obtaining independent measures of the index and the animal density; (3) evaluate the precision of the calibration (Diefenbach et al., 1994). Carbone et al. (2001) argue that the number of camera-days per photograph is a useful index of density for large, cryptic, forest-dwelling animals, and proceed to calibrate this index for tigers (Panthera tigris). We agree that a properly calibrated index may be useful for rapid assessments in conservation planning. However, Carbone et al. (2001), who desire to use their index as a substitute for density, do not adequately address the three elements noted above. Thus, we are concerned that others may view their methods as justification for not attempting directly to estimate animal densities, without due regard for the shortcomings of their approach.
Ghammraoui, Bahaa; Badal, Andreu; Popescu, Lucretiu M.
2016-04-01
Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter cross section of the investigated object revealing structural information of tissue under investigation. In the original CSCT proposals the reconstruction of images from coherently scattered x-rays is done at each scattering angle separately using analytic reconstruction. In this work we develop a maximum likelihood estimation of scatter components algorithm (ML-ESCA) that iteratively reconstructs images using a few material component basis functions from coherent scatter projection data. The proposed algorithm combines the measured scatter data at different angles into one reconstruction equation with only a few component images. Also, it accounts for data acquisition statistics and physics, modeling effects such as polychromatic energy spectrum and detector response function. We test the algorithm with simulated projection data obtained with a pencil beam setup using a new version of MC-GPU code, a Graphical Processing Unit version of PENELOPE Monte Carlo particle transport simulation code, that incorporates an improved model of x-ray coherent scattering using experimentally measured molecular interference functions. The results obtained for breast imaging phantoms using adipose and glandular tissue cross sections show that the new algorithm can separate imaging data into basic adipose and water components at radiation doses comparable with Breast Computed Tomography. Simulation results also show the potential for imaging microcalcifications. Overall, the component images obtained with ML-ESCA algorithm have a less noisy appearance than the images obtained with the conventional filtered back projection algorithm for each individual scattering angle. An optimization study for x-ray energy range selection for breast CSCT is also presented.
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
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Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
2011-05-15
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Semivariogram models for estimating fig fly population density throughout the year
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Mauricio Paulo Batistella Pasini
2014-07-01
Full Text Available The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae throughout the year, using ordinary kriging. Nineteen monitoring sites were demarcated in an area of 8,200 m2, cropped with six fruit tree species: persimmon, citrus, fig, guava, apple, and peach. During a 24 month period, 106 weekly evaluations were done in these sites. The average number of adult fig flies captured weekly per trap, during each month, was subjected to the circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, hole effect, K-Bessel, J-Bessel, and stable semivariogram models, using ordinary kriging interpolation. The models with the best fit were selected by cross-validation. Each data set (months has a particular spatial dependence structure, which makes it necessary to define specific models of semivariograms in order to enhance the adjustment to the experimental semivariogram. Therefore, it was not possible to determine a standard semivariogram model; instead, six theoretical models were selected: circular, Gaussian, hole effect, K-Bessel, J-Bessel, and stable.
Novelty detection by multivariate kernel density estimation and growing neural gas algorithm
Fink, Olga; Zio, Enrico; Weidmann, Ulrich
2015-01-01
One of the underlying assumptions when using data-based methods for pattern recognition in diagnostics or prognostics is that the selected data sample used to train and test the algorithm is representative of the entire dataset and covers all combinations of parameters and conditions, and resulting system states. However in practice, operating and environmental conditions may change, unexpected and previously unanticipated events may occur and corresponding new anomalous patterns develop. Therefore for practical applications, techniques are required to detect novelties in patterns and give confidence to the user on the validity of the performed diagnosis and predictions. In this paper, the application of two types of novelty detection approaches is compared: a statistical approach based on multivariate kernel density estimation and an approach based on a type of unsupervised artificial neural network, called the growing neural gas (GNG). The comparison is performed on a case study in the field of railway turnout systems. Both approaches demonstrate their suitability for detecting novel patterns. Furthermore, GNG proves to be more flexible, especially with respect to dimensionality of the input data and suitability for online learning.
Chan, Poh Yin; Tong, Chi Ming; Durrant, Marcus C
2011-09-01
An empirical method for estimation of the boiling points of organic molecules based on density functional theory (DFT) calculations with polarized continuum model (PCM) solvent corrections has been developed. The boiling points are calculated as the sum of three contributions. The first term is calculated directly from the structural formula of the molecule, and is related to its effective surface area. The second is a measure of the electronic interactions between molecules, based on the DFT-PCM solvation energy, and the third is employed only for planar aromatic molecules. The method is applicable to a very diverse range of organic molecules, with normal boiling points in the range of -50 to 500 °C, and includes ten different elements (C, H, Br, Cl, F, N, O, P, S and Si). Plots of observed versus calculated boiling points gave R²=0.980 for a training set of 317 molecules, and R²=0.979 for a test set of 74 molecules. The role of intramolecular hydrogen bonding in lowering the boiling points of certain molecules is quantitatively discussed. PMID:21798775
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Cristina Maria Teixeira Fortes
2014-12-01
Full Text Available OBJECTIVE: To study bone mineral density (BMD in adolescent females according to five groups of chronological age (CA, bone age (BA, and breast development stage (B, and to correlate these parameters with plasma bone biomarkers (BB. METHODS: This was a cross-sectional study performed in 101 healthy adolescent females between 10 and 20 years old. The study variables were: weight, height, body mass index (BMI, CA, B, BA, calcium intake, BMD, and BB. Osteocalcin (OC, bone alkaline phosphatase (BAP, and C-terminal telopeptide (S-CTx were evaluated for BB. BMD was measured using dual energy X-ray absorptiometry (DXA. RESULTS: BMD in lumbar spine, proximal femur, and total body increased with age, and the respective observed averages were: in CA1 (10 years old, 0.631, 0.692, 0.798 g/cm2; in CA2 (11 to 12 years old, 0.698, 0.763, 0.840 g/cm2; in CA3 (13 to 14 years old, 0.865, 0.889, 0.972 g/cm2; in CA4 (15 to 16 years old, 0.902, 0.922, 1.013 g/cm2; and in CA5 (17 to 19 years old, 0.944, 0.929, 1.35 g/cm2. These results showed significant differences between 13 and 14 years of age (CA3 or when girls reached the B3 stage (0.709, 0.832, 0.867 g/cm2. The highest median concentrations of BB were between 10 and 12 years of age when adolescents were in the B2-B3 (p < 0.001. Median BB concentrations decreased in advanced BA and B. CONCLUSIONS: BB concentrations were positively correlated with the peak height velocity and negatively correlated with BMD in the study sites. Increased BMD and BB concentrations were observed in B3.
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Low-density lipoprotein (LDL) receptors are overexpressed in most neoplastic cell lines and provide a mechanism for the internalization and concentration of drug-laden nanoemulsions that bind to these receptors. The aim of the present study was to determine whether the administration of standard chemotherapeutic schemes can alter the expression of LDL and LDL receptor-related protein 1 (LRP-1) receptors in breast carcinoma. Fragments of tumoral and normal breast tissue from 16 consecutive volunteer women with breast cancer in stage II or III were obtained from biopsies before the beginning of neoadjuvant chemotherapy and after chemotherapy, from fragments excised during mastectomy. Tissues were analyzed by immunohistochemistry for both receptors. Because complete response to treatment was achieved in 4 patients, only the tumors from 12 were analyzed. Before chemotherapy, there was overexpression of LDL receptor in the tumoral tissue compared to normal breast tissue in 8 of these patients. LRP-1 receptor overexpression was observed in tumors of 4 patients. After chemotherapy, expression of both receptors decreased in the tumors of 6 patients, increased in 4 and was unchanged in 2. Nonetheless, even when chemotherapy reduced receptors expression, the expression was still above normal. The fact that chemotherapy does not impair LDL receptors expression supports the use of drug carrier systems that target neoplastic cells by the LDL receptor endocytic pathway in patients on conventional chemotherapy
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Pires, L.A. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Hegg, R. [Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Freitas, F.R.; Tavares, E.R.; Almeida, C.P. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Baracat, E.C. [Departamento de Ginecologia, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Maranhão, R.C. [Laboratório de Metabolismo de Lípides, Instituto do Coração, Faculdade de Medicina, Hospital das Clínicas, Universidade de São Paulo, São Paulo, SP (Brazil); Faculdade de Ciências Farmacêuticas, Universidade de São Paulo, São Paulo, SP (Brazil)
2012-05-04
Low-density lipoprotein (LDL) receptors are overexpressed in most neoplastic cell lines and provide a mechanism for the internalization and concentration of drug-laden nanoemulsions that bind to these receptors. The aim of the present study was to determine whether the administration of standard chemotherapeutic schemes can alter the expression of LDL and LDL receptor-related protein 1 (LRP-1) receptors in breast carcinoma. Fragments of tumoral and normal breast tissue from 16 consecutive volunteer women with breast cancer in stage II or III were obtained from biopsies before the beginning of neoadjuvant chemotherapy and after chemotherapy, from fragments excised during mastectomy. Tissues were analyzed by immunohistochemistry for both receptors. Because complete response to treatment was achieved in 4 patients, only the tumors from 12 were analyzed. Before chemotherapy, there was overexpression of LDL receptor in the tumoral tissue compared to normal breast tissue in 8 of these patients. LRP-1 receptor overexpression was observed in tumors of 4 patients. After chemotherapy, expression of both receptors decreased in the tumors of 6 patients, increased in 4 and was unchanged in 2. Nonetheless, even when chemotherapy reduced receptors expression, the expression was still above normal. The fact that chemotherapy does not impair LDL receptors expression supports the use of drug carrier systems that target neoplastic cells by the LDL receptor endocytic pathway in patients on conventional chemotherapy.
International Nuclear Information System (INIS)
Low-density lipoprotein receptor-related protein 1 (LRP1) is a multifunctional endocytic receptor with an important role in regulating the activity of proteinases in extracellular matrix. Several studies have also described its role in intracellular signaling. Previous studies showed that the expression of LRP1 is related to invasiveness of cancer cells. However, recent data on LRP1 suggest that this receptor can also be involved in tumor establishment and progression. We investigated an association between the C766T polymorphism of the third exon of the LRP1 gene and breast cancer in a sample of women of Caucasian origin. Allele and genotype frequencies of this polymorphism were assessed in 164 women with breast cancer and in 183 age-compatible women without a history of any cancer disease. An increase in LRP1 T allele frequency in subjects with breast cancer was observed compared with controls (0.21 versus 0.15, P = 0.01963). A significant excess of genotypes with the T allele (homozygotes plus heterozygotes) was also observed (odds ratio 1.743, 95% confidence interval 1.112–2.732). The T allele of the C766T polymorphism in the LRP1 gene is associated with an increased risk of breast cancer development in women of Caucasian origin
Directory of Open Access Journals (Sweden)
W. Chen
2015-11-01
Full Text Available Drought caused the most widespread damage in China, making up over 50 % of the total affected area nationwide in recent decades. In the paper, a Standardized Precipitation Index-based (SPI-based drought risk study is conducted using historical rainfall data of 19 weather stations in Shandong province, China. Kernel density based method is adopted to carry out the risk analysis. Comparison between the bivariate Gaussian kernel density estimation (GKDE and diffusion kernel density estimation (DKDE are carried out to analyze the effect of drought intensity and drought duration. The results show that DKDE is relatively more accurate without boundary-leakage. Combined with the GIS technique, the drought risk is presented which reveals the spatial and temporal variation of agricultural droughts for corn in Shandong. The estimation provides a different way to study the occurrence frequency and severity of drought risk from multiple perspectives.
Chen, W.; Shao, Z.; Tiong, L. K.
2015-11-01
Drought caused the most widespread damage in China, making up over 50 % of the total affected area nationwide in recent decades. In the paper, a Standardized Precipitation Index-based (SPI-based) drought risk study is conducted using historical rainfall data of 19 weather stations in Shandong province, China. Kernel density based method is adopted to carry out the risk analysis. Comparison between the bivariate Gaussian kernel density estimation (GKDE) and diffusion kernel density estimation (DKDE) are carried out to analyze the effect of drought intensity and drought duration. The results show that DKDE is relatively more accurate without boundary-leakage. Combined with the GIS technique, the drought risk is presented which reveals the spatial and temporal variation of agricultural droughts for corn in Shandong. The estimation provides a different way to study the occurrence frequency and severity of drought risk from multiple perspectives.
Hearn, Andrew J.; Ross, Joanna; Bernard, Henry; Bakar, Soffian Abu; Hunter, Luke T. B.; Macdonald, David W.
2016-01-01
The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches. PMID:27007219
International Nuclear Information System (INIS)
To evaluate the accordance of size measurements of malignant breast lesions 65 women with 76 malignant lesions were preoperatively examined with triple diagnosis (mammography was performed in three views with additional views if necessary) and dynamic MR imaging using a subtraction technique with a 3D T1-weighted sequence. Maximum lesion size at histopathology was used as gold standard and compared with maximum lesion size at MRI and mammography. All measurements were made independently for each method. Histopathology verified 48 invasive, 5 in situ, and 23 mixed lesions. No significant difference was found for the pure invasive lesions (p=0.366). In the mixed lesions a slightly better result for MRI was indicated (p=0.116), although there was a great spread. Only five pure in situ lesions were assessed, too few to draw any statistical conclusions (p>0.5). An overall difference indicated a slight superiority of MRI (p=0.097). The MR imaging and mammography are both good at measuring the size of detected invasive breast malignancies. The total sizes of mixed lesions are frequently underestimated by both MRI and mammography, although the invasive parts were equally well described and measured with both methods. (orig.)
Freer, Phoebe E; Slanetz, Priscilla J; Haas, Jennifer S; Tung, Nadine M; Hughes, Kevin S; Armstrong, Katrina; Semine, A Alan; Troyan, Susan L; Birdwell, Robyn L
2015-09-01
Stemming from breast density notification legislation in Massachusetts effective 2015, we sought to develop a collaborative evidence-based approach to density notification that could be used by practitioners across the state. Our goal was to develop an evidence-based consensus management algorithm to help patients and health care providers follow best practices to implement a coordinated, evidence-based, cost-effective, sustainable practice and to standardize care in recommendations for supplemental screening. We formed the Massachusetts Breast Risk Education and Assessment Task Force (MA-BREAST) a multi-institutional, multi-disciplinary panel of expert radiologists, surgeons, primary care physicians, and oncologists to develop a collaborative approach to density notification legislation. Using evidence-based data from the Institute for Clinical and Economic Review, the Cochrane review, National Comprehensive Cancer Network guidelines, American Cancer Society recommendations, and American College of Radiology appropriateness criteria, the group collaboratively developed an evidence-based best-practices algorithm. The expert consensus algorithm uses breast density as one element in the risk stratification to determine the need for supplemental screening. Women with dense breasts and otherwise low risk (20% lifetime) should consider supplemental screening MRI in addition to routine mammography regardless of breast density. We report the development of the multi-disciplinary collaborative approach to density notification. We propose a risk stratification algorithm to assess personal level of risk to determine the need for supplemental screening for an individual woman. PMID:26290416
Chen, W.; Shao, Z; L. K. Tiong
2015-01-01
Drought caused the most widespread damage in China, making up over 50 % of the total affected area nationwide in recent decades. In the paper, a Standardized Precipitation Index-based (SPI-based) drought risk study is conducted using historical rainfall data of 19 weather stations in Shandong province, China. Kernel density based method is adopted to carry out the risk analysis. Comparison between the bivariate Gaussian kernel density estimation (GKDE) and d...
Institute of Scientific and Technical Information of China (English)
于代友; 刘秀梅; 陈雯; 冯娜娜; 于洁; 吴月清; 刘红娟
2015-01-01
Objective It is to analyze the relevance between the structure of female breast density and physiology, repro-ductive characteristics and breast cancer.Methods 5006 cases of local women with complete data whom had accepted digital breast X-ray angiography were selected.ACR BI-RADS was used as standard to evaluate mammary gland density type.Be-sides, breast cancer was diagnosed on the basis of pathological diagnosis.In the study, all data was divided according to phys-iology and reproductive characteristics, and the composing and correlation between breast cancer and breast density was ana-lyzed.Results The average age was 44.22 ±8.09 and median age was 43.Constitution of the mammary gland density in 5 006:lard type 256(5.11%), small type 726(14.51%), quantity type 3719(74.29%), and density type 305(6.09%).There was statistically significant difference between breast density and age, lactation history, history of abortion, menopause age, sterilization etc(P0.05).Pathology confirmed breast cancer 184 cases, constitution of the mammary gland density:lard type 26(14.13%), small type 66(35.87%), quantity type 91(49.46%)and density type 1(0.54%). Significant statistically difference was found between mammary gland density and age, menopause age, whether take strogen etc(P0.05).Conclusion The important factors that affect female breast density showing as follows:age, lactation history, history of abortion, menopause age, whether done sterilization, nev-ertheless, age, menopause women and low density of breast could increase the risk .%目的：分析女性乳腺密度的构成与生理、生育因素及乳腺癌之间相关性。方法选取接受全数字乳腺X射线摄影检查且临床资料完整的当地女性5006例，以ACR BI－RADS标准，依据乳腺X射线摄影结果评价乳腺腺体密度类型，乳腺癌以病理诊断为标准。按不同年龄、生育特征因素分组，分析其与乳腺密度构成及乳腺癌之间相关性。结果5006
Karanth, K.U.; Chundawat, R.S.; Nichols, J.D.; Kumar, N.S.
2004-01-01
Tropical dry-deciduous forests comprise more than 45% of the tiger (Panthera tigris) habitat in India. However, in the absence of rigorously derived estimates of ecological densities of tigers in dry forests, critical baseline data for managing tiger populations are lacking. In this study tiger densities were estimated using photographic capture?recapture sampling in the dry forests of Panna Tiger Reserve in Central India. Over a 45-day survey period, 60 camera trap sites were sampled in a well-protected part of the 542-km2 reserve during 2002. A total sampling effort of 914 camera-trap-days yielded photo-captures of 11 individual tigers over 15 sampling occasions that effectively covered a 418-km2 area. The closed capture?recapture model Mh, which incorporates individual heterogeneity in capture probabilities, fitted these photographic capture history data well. The estimated capture probability/sample, 0.04, resulted in an estimated tiger population size and standard error of 29 (9.65), and a density of 6.94 (3.23) tigers/100 km2. The estimated tiger density matched predictions based on prey abundance. Our results suggest that, if managed appropriately, the available dry forest habitat in India has the potential to support a population size of about 9000 wild tigers.
Trenkel, Verena M.; Lorance, Pascal
2011-01-01
Kaup's arrowtooth eel Synaphobranchus kaupii is a small-bodied fish and an abundant inhabitant of the European continental slope. To estimate its local density video information using the remotely operated vehicle (ROV) Victor 6000 were collected at three locations in the Bay of Biscay slope. Two methods for estimating local densities were tested: strip transect counts and bait experiments. For bait experiments three behaviour types were observed in about equal proportions for individuals arriving near the seafloor: moving up the current towards the ROV, moving across the current and drifting with the current. Visible attraction towards the bait was the highest for individuals swimming against the current (80%) and about equally low for the other two types (around 30%); it did not depend on current speed nor temperature. Three main innovations were introduced for estimating population densities from bait experiments: (i) inclusion of an additional behaviour category—that of passively drifting individuals, (ii) inclusion of reaction behaviour for actively swimming individuals and (iii) a hierarchical Bayesian estimation framework. The results indicated that about half of individuals were foraging actively of which less than one third reacted on encountering the bait plume and the other half were drifting with the current. Taking account of drifting individuals and the reaction probability made density estimates from bait experiments and strip transects more similar.
Trolle, M.; Kery, M.
2003-01-01
Neotropical felids such as the ocelot (Leopardus pardalis) are secretive, and it is difficult to estimate their populations using conventional methods such as radiotelemetry or sign surveys. We show that recognition of individual ocelots from camera-trapping photographs is possible, and we use camera-trapping results combined with closed population capture-recapture models to estimate density of ocelots in the Brazilian Pantanal. We estimated the area from which animals were camera trapped at 17.71 km2. A model with constant capture probability yielded an estimate of 10 independent ocelots in our study area, which translates to a density of 2.82 independent individuals for every 5 km2 (SE 1.00).
Institute of Scientific and Technical Information of China (English)
陈清平; 戴永隆
2003-01-01
Based on left truncated and right censored dependent data, the estimatorsof higher derivatives of density function and hazard rate function are given by kernelsmoothing method. When observed data exhibit α-mixing dependence, local propertiesincluding strong consistency and law of iterated logarithm are presented. Moreover, whenthe mode estimator is defined as the random variable that maximizes the kernel densityestimator, the asymptotic normality of the mode estimator is established.
International Nuclear Information System (INIS)
Background: The Icelandic breast cancer screening program, initiated November 1987 in Reykjavik and covering the whole country from December 1989, comprises biennial invitation to mammography for women aged 40-69 years old. Purpose: To estimate the impact of mammography service screening in Iceland on deaths from breast cancer. Material and Methods: Cases were deaths from breast cancer from 1990 onwards in women aged 40 and over at diagnosis, during the period November 1987 to December 31, 2002. Age- and screening-area-matched, population-based controls were women who had also been invited to screening but were alive at the time their case died. Results: Using conditional logistic regression on the data from 226 cases and 902 controls, the odds ratio for the risk of death from breast cancer in those attending at least one screen compared to those never screened was 0.59 (95% CI 0.41-0.84). After adjustment for healthy-volunteer bias and screening-opportunity bias, the odds ratio was 0.65 (95% CI 0.39-1.09). Conclusion: These results indicate a 35-40% reduction in breast cancer deaths by attending the Icelandic breast cancer screening program. These results are consistent with the overall evidence from other observational evaluations of mammography-based programs
Keogh, Ruth H; Park, Jin Young; White, Ian R; Lentjes, Marleen A H; McTaggart, Alison; Bhaniani, Amit; Cairns, Benjamin J; Key, Timothy J; Greenwood, Darren C; Burley, Victoria J; Cade, Janet E; Dahm, Christina C; Pot, Gerda K; Stephen, Alison M; Masset, Gabriel; Brunner, Eric J; Khaw, Kay-Tee
2012-07-01
The alcohol-breast cancer association has been established using alcohol intake measurements from Food Frequency Questionnaires (FFQ). For some nutrients diet diary measurements are more highly correlated with true intake compared with FFQ measurements, but it is unknown whether this is true for alcohol. A case-control study (656 breast cancer cases, 1905 matched controls) was sampled from four cohorts in the UK Dietary Cohort Consortium. Alcohol intake was measured prospectively using FFQs and 4- or 7-day diet diaries. Both relied on fixed portion sizes allocated to given beverage types, but those used to obtain FFQ measurements were lower. FFQ measurements were therefore on average lower and to enable fair comparison the FFQ was "calibrated" using diet diary portion sizes. Diet diaries gave more zero measurements, demonstrating the challenge of distinguishing never-from episodic-consumers using short term instruments. To use all information, two combined measurements were calculated. The first is an average of the two measurements with special treatment of zeros. The second is the expected true intake given both measurements, calculated using a measurement error model. After confounder adjustment the odds ratio (OR) per 10 g/day of alcohol intake was 1.05 (95 % CI 0.98, 1.13) using diet diaries, and 1.13 (1.02, 1.24) using FFQs. The calibrated FFQ measurement and combined measurements 1 and 2 gave ORs 1.10 (1.03, 1.18), 1.09 (1.01, 1.18), 1.09 (0.99,1.20), respectively. The association was modified by HRT use, being stronger among users versus non-users. In summary, using an alcohol measurement from a diet diary at one time point gave attenuated associations compared with FFQ. PMID:22644108
International Nuclear Information System (INIS)
For nearly 80 years that radium has been used for the treatment of malignancy, the method of dose control have progressed toward a more detailed description of the radiation distribution as permitted by the knowledge and technology of the time. Although the early unit of milligram-hour reveals nothing of the dose distribution, it is still used for some advantages such as a rough indicator of patient tolerance to radiation. We carried out this study on the comparison between two tumor dosages calculated from the TLD system and the Paterson-Parker system in a case of breast cancer successfully treated by us with radium needles several years ago. Case; M.T. a female aged 76 years, was seen on March 30, 1973 for an extensive carcinoma of the left breast. On June 12, 1973 radium needles were put on a tumor dose of 5,550 miligram-hour for twenty-five days. Four months later, the tumor disappeared and has not recured to date. Dose values calculated from the chips of MSO-S type (TLD system) at a distance of 10 mm from radium needles were in the range of 27.24 - 50.06 R, averaged 39.34 R per hour. Therefore, the total radiation dose values were approximately 10,000 R (9,800 rads). Dose values calculated from Paterson-Parker system in this case were 9,700 rads, therefore, these values are approximately equivalent to the values from TLD system. We pointed out that the dose values in this case are more than those reported by many investigators probably due to greater tumor than usual. (author)
International Nuclear Information System (INIS)
The estimation of the absorbed dose to the breast is an important part of the quality control of the mammographic examination. Knowledge of breast dose is essential for the design and performance assessment of mammographic imaging systems. This review gives a historical introduction to the measurement of breast dose. The mean glandular dose (MGD) is introduced as an appropriate measure of breast dose. MGD can be estimated from measurements of the incident air kerma at the surface of the breast and the application of an appropriate conversion factor. Methods of calculating and measuring this conversion factor are described and the results discussed. The incident air kerma itself may be measured for patients or for a test phantom simulating the breast. In each case the dose may be determined using TLD measurements, or known exposure parameters and measurements of tube output. The methodology appropriate to each case is considered and the results from sample surveys of breast dose are presented. Finally the various national protocols for breast dosimetry are compared
Tosic Golo, Natasa; Wal, van der Siebrigje; Kuper, F.G.; Mouthaan, A.J.
2002-01-01
The objective of this letter is to give an estimation of the impact of an electrostatic discharge (ESD) stress on the density of states (DOS) within the energy gap of hydrogenated amorphous silicon (a-Si:H) thin-film transistors. ESD stresses were applied by means of a transmission line model tester
JOURNAL NRMRL-RTP-P- 437 Baugh, W., Klinger, L., Guenther, A., and Geron*, C.D. Measurement of Oak Tree Density with Landsat TM Data for Estimating Biogenic Isoprene Emissions in Tennessee, USA. International Journal of Remote Sensing (Taylor and Francis) 22 (14):2793-2810 (2001)...
Institute of Scientific and Technical Information of China (English)
ZHANG Baoqiang; CHEN Guoping; GUO Qintao
2012-01-01
An improved method using kernel density estimation (KDE) and confidence level is presented for model validation with small samples.Decision making is a challenging problem because of input uncertainty and only small samples can be used due to the high costs of experimental measurements.However,model validation provides more confidence for decision makers when improving prediction accuracy at the same time.The confidence level method is introduced and the optimum sample variance is determined using a new method in kernel density estimation to increase the credibility of model validation.As a numerical example,the static frame model validation challenge problem presented by Sandia National Laboratories has been chosen.The optimum bandwidth is selected in kernel density estimation in order to build the probability model based on the calibration data.The model assessment is achieved using validation and accreditation experimental data respectively based on the probability model.Finally,the target structure prediction is performed using validated model,which are consistent with the results obtained by other researchers.The results demonstrate that the method using the improved confidence level and kernel density estimation is an effective approach to solve the model validation problem with small samples.
Energy Technology Data Exchange (ETDEWEB)
Tang, Robert Y., E-mail: rx-tang@laurentian.ca [Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); Laamanen, Curtis, E-mail: cx-laamanen@laurentian.ca; McDonald, Nancy, E-mail: mcdnancye@gmail.com [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); LeClair, Robert J., E-mail: rleclair@laurentian.ca [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada and Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)
2014-05-15
Purpose: Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients μ{sub s} of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model. Methods: Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm{sup 2} by 1 mm thick CdTe detector allowed measurements of a portion of the θ = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N{sub 0}(E) needed in the calculations of μ{sub s}[x(E, θ)] where x is the momentum transfer argument. Values of μ{sup ¯}{sub s} for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum μ{sup ¯}{sub s}{sup ∑}(x)=ν{sub 1}μ{sub s1}(x)+ν{sub 2}μ{sub s2}(x)+ν{sub 3}μ{sub s3}(x), where ν{sub i} is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the μ{sub s} of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions. Results: The well known μ{sub s} signal of water was reproduced effectively between 0.5 < x < 1.6 nm{sup −1}. The μ{sup ¯}{sub s} obtained for the heterogeneous samples agreed with μ{sup ¯}{sub s}{sup ∑}. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies. Conclusions: The methodology to
Maadooliat, Mehdi
2015-10-21
This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.
The prognostic relevance of estimates of proliferative activity in early breast cancer
DEFF Research Database (Denmark)
Offersen, B V; Sørensen, Flemming Brandt; Knoop, A; Overgaard, J
2003-01-01
AIMS: Immunohistochemical estimates of cell proliferation evaluated with MIB-1 antibody have been suggested as prognostic indicators in different types of carcinoma. This study investigates whether MIB-1 scores add additional prognostic impact when evaluated together with classical clinicopatholo...
Cavada, Nathalie; Barelli, Claudia; Ciolli, Marco; Rovero, Francesco
2016-01-01
Accurate density estimations of threatened animal populations is essential for management and conservation. This is particularly critical for species living in patchy and altered landscapes, as is the case for most tropical forest primates. In this study, we used a hierarchical modelling approach that incorporates the effect of environmental covariates on both the detection (i.e. observation) and the state (i.e. abundance) processes of distance sampling. We applied this method to already published data on three arboreal primates of the Udzungwa Mountains of Tanzania, including the endangered and endemic Udzungwa red colobus (Procolobus gordonorum). The area is a primate hotspot at continental level. Compared to previous, 'canonical' density estimates, we found that the inclusion of covariates in the modelling makes the inference process more informative, as it takes in full account the contrasting habitat and protection levels among forest blocks. The correction of density estimates for imperfect detection was especially critical where animal detectability was low. Relative to our approach, density was underestimated by the canonical distance sampling, particularly in the less protected forest. Group size had an effect on detectability, determining how the observation process varies depending on the socio-ecology of the target species. Lastly, as the inference on density is spatially-explicit to the scale of the covariates used in the modelling, we could confirm that primate densities are highest in low-to-mid elevations, where human disturbance tend to be greater, indicating a considerable resilience by target monkeys in disturbed habitats. However, the marked trend of lower densities in unprotected forests urgently calls for effective forest protection. PMID:26844891
Directory of Open Access Journals (Sweden)
Park Jinho
2012-06-01
Full Text Available Abstract Background Myocardial ischemia can be developed into more serious diseases. Early Detection of the ischemic syndrome in electrocardiogram (ECG more accurately and automatically can prevent it from developing into a catastrophic disease. To this end, we propose a new method, which employs wavelets and simple feature selection. Methods For training and testing, the European ST-T database is used, which is comprised of 367 ischemic ST episodes in 90 records. We first remove baseline wandering, and detect time positions of QRS complexes by a method based on the discrete wavelet transform. Next, for each heart beat, we extract three features which can be used for differentiating ST episodes from normal: 1 the area between QRS offset and T-peak points, 2 the normalized and signed sum from QRS offset to effective zero voltage point, and 3 the slope from QRS onset to offset point. We average the feature values for successive five beats to reduce effects of outliers. Finally we apply classifiers to those features. Results We evaluated the algorithm by kernel density estimation (KDE and support vector machine (SVM methods. Sensitivity and specificity for KDE were 0.939 and 0.912, respectively. The KDE classifier detects 349 ischemic ST episodes out of total 367 ST episodes. Sensitivity and specificity of SVM were 0.941 and 0.923, respectively. The SVM classifier detects 355 ischemic ST episodes. Conclusions We proposed a new method for detecting ischemia in ECG. It contains signal processing techniques of removing baseline wandering and detecting time positions of QRS complexes by discrete wavelet transform, and feature extraction from morphology of ECG waveforms explicitly. It was shown that the number of selected features were sufficient to discriminate ischemic ST episodes from the normal ones. We also showed how the proposed KDE classifier can automatically select kernel bandwidths, meaning that the algorithm does not require any numerical
Energy Technology Data Exchange (ETDEWEB)
Lin Muqing; Chen, Jeon-Hor; Bahri, Shadfar; Nalcioglu, Orhan; Su Minying [Tu and Yuen Center for Functional Onco-Imaging, Department of Radiological Sciences, University of California, Irvine, CA (United States); Mehta, Rita S [Department of Medicine, University of California, Irvine, CA (United States); Chan Siwa, E-mail: msu@uci.edu [Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan (China)
2011-09-21
Breast MRI acquires many images from the breast, and computer-aided algorithms and display tools are often used to assist the radiologist's interpretation. Women with lifetime risk greater than 20% of developing breast cancer are recommended to receive annual screening MRI, but the current breast MRI computer-aided-diagnosis systems do not provide the necessary function for comparison of images acquired at different times. The purpose of this work was to develop registration methods for evaluating the spatial change pattern of fibroglandular tissue between two breast MRI scans of the same woman taken at different times. The registration method is based on rigid alignment followed by a non-rigid Demons algorithm. The method was tested on three different subjects who had different degrees of changes in the fibroglandular tissue, including two patients who showed different spatial shrinkage patterns after receiving neoadjuvant chemotherapy before surgery, and one control case from a normal volunteer. Based on the transformation matrix, the collapse of multiple voxels on the baseline images to one voxel on the follow-up images is used to calculate the shrinkage factor. Conversely, based on the reverse transformation matrix the expansion factor can be calculated. The shrinkage/expansion factor, the deformation magnitude and direction, as well as the Jacobian determinate at each location can be displayed in a 3D rendering view to show the spatial changes between two MRI scans. These different parameters show consistent results and can be used for quantitative evaluation of the spatial change patterns. The presented registration method can be further developed into a clinical tool for evaluating therapy-induced changes and for early diagnosis of breast cancer in screening MRI.
International Nuclear Information System (INIS)
Breast MRI acquires many images from the breast, and computer-aided algorithms and display tools are often used to assist the radiologist's interpretation. Women with lifetime risk greater than 20% of developing breast cancer are recommended to receive annual screening MRI, but the current breast MRI computer-aided-diagnosis systems do not provide the necessary function for comparison of images acquired at different times. The purpose of this work was to develop registration methods for evaluating the spatial change pattern of fibroglandular tissue between two breast MRI scans of the same woman taken at different times. The registration method is based on rigid alignment followed by a non-rigid Demons algorithm. The method was tested on three different subjects who had different degrees of changes in the fibroglandular tissue, including two patients who showed different spatial shrinkage patterns after receiving neoadjuvant chemotherapy before surgery, and one control case from a normal volunteer. Based on the transformation matrix, the collapse of multiple voxels on the baseline images to one voxel on the follow-up images is used to calculate the shrinkage factor. Conversely, based on the reverse transformation matrix the expansion factor can be calculated. The shrinkage/expansion factor, the deformation magnitude and direction, as well as the Jacobian determinate at each location can be displayed in a 3D rendering view to show the spatial changes between two MRI scans. These different parameters show consistent results and can be used for quantitative evaluation of the spatial change patterns. The presented registration method can be further developed into a clinical tool for evaluating therapy-induced changes and for early diagnosis of breast cancer in screening MRI.
Palmer, Jason Allan
2006-01-01
This thesis considers representations of non-Gaussian probability densities for use in various estimation problems associated with the Bayesian Linear Model. We define a class of densities that we call Strongly Super- Gaussian, and show the relationship of these densities to Gaussian Scale Mixtures, and densities with positive kurtosis. Such densities have been used to model "sparse" random variables, with densities that are sharply peaked with heavy tails. We show that strongly super-Gaussia...
Directory of Open Access Journals (Sweden)
Jianlei Kong
2015-07-01
Full Text Available In this paper, a new algorithm to improve the accuracy of estimating diameter at breast height (DBH for tree trunks in forest areas is proposed. First, the information is collected by a two-dimensional terrestrial laser scanner (2DTLS, which emits laser pulses to generate a point cloud. After extraction and filtration, the laser point clusters of the trunks are obtained, which are optimized by an arithmetic means method. Then, an algebraic circle fitting algorithm in polar form is non-linearly optimized by the Levenberg-Marquardt method to form a new hybrid algorithm, which is used to acquire the diameters and positions of the trees. Compared with previous works, this proposed method improves the accuracy of diameter estimation of trees significantly and effectively reduces the calculation time. Moreover, the experimental results indicate that this method is stable and suitable for the most challenging conditions, which has practical significance in improving the operating efficiency of forest harvester and reducing the risk of causing accidents.
International Nuclear Information System (INIS)
Hamartoma of the breast is a rare circumscribed lesion composed of fat and other breast tissue which may be normal or which may show various benign changes. Pathognomonic mammographic features are non-homogenous mass containing mottled densities corresponding to fat, epithelium and connective tissue. In this report, radiological, pathological and histological findings are described. The lesions are usually diagnosed radiologically and accurate diagnosis is necessary for the patient's management and prognosis
mBEEF-vdW: Robust fitting of error estimation density functionals
DEFF Research Database (Denmark)
Lundgård, Keld Troen; Wellendorff, Jess; Voss, Johannes;
2016-01-01
. The functional is fitted within the Bayesian error estimation functional (BEEF) framework [J. Wellendorff et al., Phys. Rev. B 85, 235149 (2012); J. Wellendorff et al., J. Chem. Phys. 140, 144107 (2014)]. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss...... function, reducing the sensitivity to outliers in the datasets. To more reliably determine the optimal model complexity, we furthermore introduce a generalization of the bootstrap 0.632 estimator with hierarchical bootstrap sampling and geometric mean estimator over the training datasets. Using this...
Estimation of the density of Martian soil from radiophysical measurements in the 3-centimeter range
Krupenio, N. N.
1977-01-01
The density of the Martian soil is evaluated at a depth up to one meter using the results of radar measurement at lambda sub 0 = 3.8 cm and polarized radio astronomical measurement at lambda sub 0 = 3.4 cm conducted onboard the automatic interplanetary stations Mars 3 and Mars 5. The average value of the soil density according to all measurements is rho bar = 1.37 plus or minus 0.33 g/ cu cm. A map of the distribution of the permittivity and soil density is derived, which was drawn up according to radiophysical data in the 3 centimeter range.
Lingling Jiang; Lin Wang; Xinyu Zhang; Yanlong Chen; Deqi Xiong
2016-01-01
A multiband and a single-band semianalytical model were developed to predict algae cell density distribution. The models were based on cell density (N) dependent parameterizations of the spectral backscattering coefficients, bb(λ), obtained from in situ measurements. There was a strong relationship between bb(λ) and N, with a minimum regression coefficient of 0.97 at 488 nm and a maximum value of 0.98 at other bands. The cell density calculated by the multiband inversion model was similar to ...
De Marco, Stefano
2011-01-01
We study smoothness of densities for the solutions of SDEs whose coefficients are smooth and nondegenerate only on an open domain $D$. We prove that a smooth density exists on $D$ and give upper bounds for this density. Under some additional conditions (mainly dealing with the growth of the coefficients and their derivatives), we formulate upper bounds that are suitable to obtain asymptotic estimates of the density for large values of the state variable ("tail" estimates). These results specify and extend some results by Kusuoka and Stroock [J. Fac. Sci. Univ. Tokyo Sect. IA Math. 32 (1985) 1--76], but our approach is substantially different and based on a technique to estimate the Fourier transform inspired from Fournier [Electron. J. Probab. 13 (2008) 135--156] and Bally [Integration by parts formula for locally smooth laws and applications to equations with jumps I (2007) The Royal Swedish Academy of Sciences]. This study is motivated by existing models for financial securities which rely on SDEs with non-...
Directory of Open Access Journals (Sweden)
Pablo García
2009-04-01
Full Text Available Because of the crucial importance for otter ecology and conservation, estimating population size (or standardizing it in density is one of the major fields of research. However, the behaviour of the species makes estimates complicated. The vast majority of methods rely on the study of signs (mainly spraints, but also tracks, but this is insufficient for density measurements, or too costly. Other techniques with proven results use visual counts of otters, but they also have some faults and involve a disproportionate sampling effort. The encounter-based method of population estimation, proposed by Rowcliffe et al. (2008, has been applied to otter sightings in two sites of different habitat with known otter density, and under different survey designs. This provisional check appears to confirm that the method results in adequate population estimates, also when employing samples at random intervals of time and space. Moreover, it involves lower effort, and the census can be tackled by a reduced number of researchers. It is strongly suggested that this methodology be widely tested, to ascertain its performance under different sampling and environmental conditions.
Analysis of the Influence of Plot Size and LiDAR Density on Forest Structure Attribute Estimates
Directory of Open Access Journals (Sweden)
Luis A. Ruiz
2014-05-01
Full Text Available This paper assesses the combined effect of field plot size and LiDAR density on the estimation of four forest structure attributes: volume, total biomass, basal area and canopy cover. A total of 21 different plot sizes were considered, obtained by decreasing the field measured plot radius value from 25 to 5 m with regular intervals of 1 m. LiDAR data densities were simulated by randomly removing LiDAR pulses until reaching nine different density values. In order to avoid influence of the digital terrain model spatial resolution, eight different resolutions were considered (from 0.25 to 2 m grid size and tested. A set of per-plot LiDAR metrics was extracted for each parameter combination. Prediction models of forest attributes were defined using forward stepwise ordinary least-square regressions. Results show that the highest R2 values are reached by combining large plot sizes and high LiDAR data density values. However, plot size has a greater effect than LiDAR point density. In general, minimum plot areas of 500–600 m2 are needed for volume, biomass and basal area estimates, and of 300–400 m2 for canopy cover. Larger plot sizes do not significantly increase the accuracy of the models, but they increase the cost of fieldwork.