Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

Identifiability of diffusion and sorption parameters from in situ diffusion experiments by using simultaneously tracer dilution and claystone data

In situ diffusion experiments are performed in geological formations at underground research laboratories to overcome the limitations of laboratory diffusion experiments and investigate scale effects. Tracer concentrations are monitored at the injection interval during the experiment (dilution data) and measured from host rock samples around the injection interval at the end of the experiment (overcoring data). Diffusion and sorption parameters are derived from the inverse numerical modeling of the measured tracer data. The identifiability and the uncertainties of tritium and Na-22(+) diffusion and sorption parameters are studied here by synthetic experiments having the same characteristics as the in situ diffusion and retention (DR) experiment performed on Opalinus Clay. Contrary to previous identifiability analyses of in situ diffusion experiments, which used either dilution or overcoring data at approximate locations, our analysis of the parameter identifiability relies simultaneously on dilution and overcoring data, accounts for the actual position of the overcoring samples in the claystone, uses realistic values of the standard deviation of the measurement errors, relies on model identification criteria to select the most appropriate hypothesis about the existence of a borehole disturbed zone and addresses the effect of errors in the location of the sampling profiles. The simultaneous use of dilution and overcoring data provides accurate parameter estimates in the presence of measurement errors, allows the identification of the right hypothesis about the borehole disturbed zone and diminishes other model uncertainties such as those caused by errors in the volume of the circulation system and the effective diffusion coefficient of the filter. The proper interpretation of the experiment requires the right hypothesis about the borehole disturbed zone. A wrong assumption leads to large estimation errors. The use of model identification criteria helps in the selection of the best model. Small errors in the depth of the overcoring samples lead to large parameter estimation errors. Therefore, attention should be paid to minimize the errors in positioning the depth of the samples. The results of the identifiability analysis do not depend on the particular realization of random numbers. (C) 2012 Elsevier B.V. All rights reserved.

Prescriptions of Chinese medicinal herbs in Switzerland: the example of suan zao ren (Ziziphi Spinosae Semen)

Introduction According to the Swiss Health Survey 2007, 1.7% of the adult population use traditional Chinese medicine (including Chinese herbal medicine, but excluding acupuncture). In contrast to conventional drugs, that contain single chemically defined substances, prescriptions of Chinese herbs are mixtures of up to 40 ingredients (parts of plants, fungi, animal substances and minerals). Originally they were taken in the form of decoctions, but nowadays granules are more popular. Medium daily dosages of granules range between 8 to 12g. In a recent work we identified the most commonly used Chinese herbs (all ingredients are referred to as herbs for reasons of simplicity) and classical formulas (mixtures). Here we present a short overview and the example of suan zao ren (Ziziphi Spinosae Semen), which is used in the treatment of insomnia and anxiety and contains saponins that have been shown to increase sleep in animal studies. Material and Methods A random sample of 1,053 prescriptions was drawn from the database of Lian Chinaherb AG, Switzerland, and analysed according to the most frequently used individual herbs and classical formulas. Cluster analysis (Jaccard similarity coefficient, complete linkage method) was applied to identify common combinations of herbs. Results The most frequently used herbs were dang gui (Angelicae Sinensis Radix), fu ling (Poria), bai shao (Paeoniae Radix Alba), and gan cao (Glycyrrhizae Radix et Rhizoma); the most frequently used classical formulas were gui pi tang (Restore the Spleen Decoction) and xiao yao san (Rambling Powder). The average number of herbs per prescription was 12.0, and the average daily dosage of granules was 8.7g. 74.3% of the prescriptions were for female, 24.8% for male patients. Suan zao ren was present in 14.2% of all prescriptions. These prescriptions contained on average 13.7 herbs, and the daily dosage of granules was 8.9g. Suan zao ren was more frequently prescribed by practitioners of non-Asian than of Asian origin but equally often for female and male patients. Cluster analysis grouped suan zao ren with yuan zhi (Polygalae Radix), bai zi ren (Platycladi Semen), sheng di huang (Rehmanniae Radix) and dan shen (Salviae Miltiorrhizae Radix et Rhizoma). Discussion Prescriptions including suan zao ren contained on average slightly more herbs than other prescriptions. This might be due to the fact that two of the three most popular classical formulas with suan zao ren are composed of 13 and 12 herbs with the possibility of adding more ingredients when necessary. Cluster analysis resulted in the clustering of suan zao ren with other herbs of the classical formula tian wang bu xin dan (Emperor of Heaven’s Special Pill to Tonify the Heart), indicating the use of suan zao ren for the treatment of insomnia and irritability. Unfortunately, the diagnoses of the patients were unavailable and thus correlations between use of suan zao ren and diseases could not be analysed.

Applications of random set theory in econometrics

In recent years, the econometrics literature has shown a growing interest in the study of partially identified models, in which the object of economic and statistical interest is a set rather than a point. The characterization of this set and the development of consistent estimators and inference procedures for it with desirable properties are the main goals of partial identification analysis. This review introduces the fundamental tools of the theory of random sets, which brings together elements of topology, convex geometry, and probability theory to develop a coherent mathematical framework to analyze random elements whose realizations are sets. It then elucidates how these tools have been fruitfully applied in econometrics to reach the goals of partial identification analysis.

Virtual tissue alignment and cutting plane definition--a new method to obtain optimal longitudinal histological sections.

Histomorphometric evaluation of the buccal aspects of periodontal tissues in rodents requires reproducible alignment of maxillae and highly precise sections containing central sections of buccal roots; this is a cumbersome and technically sensitive process due to the small specimen size. The aim of the present report is to describe and analyze a method to transfer virtual sections of micro-computer tomographic (CT)-generated image stacks to the microtome for undecalcified histological processing and to describe the anatomy of the periodontium in rat molars. A total of 84 undecalcified sections of all buccal roots of seven untreated rats was analyzed. The accuracy of section coordinate transfer from virtual micro-CT slice to the histological slice, right-left side differences and the measurement error for linear and angular measurements on micro-CT and on histological micrographs were calculated using the Bland-Altman method, interclass correlation coefficient and the method of moments estimator. Also, manual alignment of the micro-CT-scanned rat maxilla was compared with multiplanar computer-reconstructed alignment. The supra alveolar rat anatomy is rather similar to human anatomy, whereas the alveolar bone is of compact type and the keratinized gingival epithelium bends apical to join the junctional epithelium. The high methodological standardization presented herein ensures retrieval of histological slices with excellent display of anatomical microstructures, in a reproducible manner, minimizes random errors, and thereby may contribute to the reduction of number of animals needed.

Reproducibility and accuracy of linear measurements on dental models derived from cone-beam computed tomography compared with digital dental casts.

INTRODUCTION The aim of this study was to determine the reproducibility and accuracy of linear measurements on 2 types of dental models derived from cone-beam computed tomography (CBCT) scans: CBCT images, and Anatomodels (InVivoDental, San Jose, Calif); these were compared with digital models generated from dental impressions (Digimodels; Orthoproof, Nieuwegein, The Netherlands). The Digimodels were used as the reference standard. METHODS The 3 types of digital models were made from 10 subjects. Four examiners repeated 37 linear tooth and arch measurements 10 times. Paired t tests and the intraclass correlation coefficient were performed to determine the reproducibility and accuracy of the measurements. RESULTS The CBCT images showed significantly smaller intraclass correlation coefficient values and larger duplicate measurement errors compared with the corresponding values for Digimodels and Anatomodels. The average difference between measurements on CBCT images and Digimodels ranged from -0.4 to 1.65 mm, with limits of agreement values up to 1.3 mm for crown-width measurements. The average difference between Anatomodels and Digimodels ranged from -0.42 to 0.84 mm with limits of agreement values up to 1.65 mm. CONCLUSIONS Statistically significant differences between measurements on Digimodels and Anatomodels, and between Digimodels and CBCT images, were found. Although the mean differences might be clinically acceptable, the random errors were relatively large compared with corresponding measurements reported in the literature for both Anatomodels and CBCT images, and might be clinically important. Therefore, with the CBCT settings used in this study, measurements made directly on CBCT images and Anatomodels are not as accurate as measurements on Digimodels.

Towards the continuum limit in transport coefficient computations

The analytic continuation needed for the extraction of transport coefficients necessitates in principle a continuous function of the Euclidean time variable. We report on progress towards achieving the continuum limit for 2-point correlator measurements in thermal SU(3) gauge theory, with specific attention paid to scale setting. In particular, we improve upon the determination of the critical lattice coupling and the critical temperature of pure SU(3) gauge theory, estimating r0Tc ≃ 0.7470(7) after a continuum extrapolation. As an application the determination of the heavy quark momentum diffusion coefficient from a correlator of colour-electric fields attached to a Polyakov loop is discussed.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

Active surveillance for rheumatic heart disease in endemic regions: a systematic review and meta-analysis of prevalence among children and adolescents

BACKGROUND Rheumatic heart disease accounts for up to 250 000 premature deaths every year worldwide and can be regarded as a physical manifestation of poverty and social inequality. We aimed to estimate the prevalence of rheumatic heart disease in endemic countries as assessed by different screening modalities and as a function of age. METHODS We searched Medline, Embase, the Latin American and Caribbean System on Health Sciences Information, African Journals Online, and the Cochrane Database of Systematic Reviews for population-based studies published between Jan 1, 1993, and June 30, 2014, that reported on prevalence of rheumatic heart disease among children and adolescents (≥5 years to <18 years). We assessed prevalence of clinically silent and clinically manifest rheumatic heart disease in random effects meta-analyses according to screening modality and geographical region. We assessed the association between social inequality and rheumatic heart disease with the Gini coefficient. We used Poisson regression to analyse the effect of age on prevalence of rheumatic heart disease and estimated the incidence of rheumatic heart disease from prevalence data. FINDINGS We included 37 populations in the systematic review and meta-analysis. The pooled prevalence of rheumatic heart disease detected by cardiac auscultation was 2·9 per 1000 people (95% CI 1·7-5·0) and by echocardiography it was 12·9 per 1000 people (8·9-18·6), with substantial heterogeneity between individual reports for both screening modalities (I(2)=99·0% and 94·9%, respectively). We noted an association between social inequality expressed by the Gini coefficient and prevalence of rheumatic heart disease (p=0·0002). The prevalence of clinically silent rheumatic heart disease (21·1 per 1000 people, 95% CI 14·1-31·4) was about seven to eight times higher than that of clinically manifest disease (2·7 per 1000 people, 1·6-4·4). Prevalence progressively increased with advancing age, from 4·7 per 1000 people (95% CI 0·0-11·2) at age 5 years to 21·0 per 1000 people (6·8-35·1) at 16 years. The estimated incidence was 1·6 per 1000 people (0·8-2·3) and remained constant across age categories (range 2·5, 95% CI 1·3-3·7 in 5-year-old children to 1·7, 0·0-5·1 in 15-year-old adolescents). We noted no sex-related differences in prevalence (p=0·829). INTERPRETATION We found a high prevalence of rheumatic heart disease in endemic countries. Although a reduction in social inequalities represents the cornerstone of community-based prevention, the importance of early detection of silent rheumatic heart disease remains to be further assessed. FUNDING UBS Optimus Foundation.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.