Compressed sensing in digital tomosynthesis reconstruction

In this work we study a model for the breast image reconstruction in Digital Tomosynthesis, that is a non-invasive and non-destructive method for the three-dimensional visualization of the inner structures of an object, in which the data acquisition includes measuring a limited number of low-dose two-dimensional projections of an object by moving a detector and an X-ray tube around the object within a limited angular range. The problem of reconstructing 3D images from the projections provided in the Digital Tomosynthesis is an ill-posed inverse problem, that leads to a minimization problem with an object function that contains a data fitting term and a regularization term. The contribution of this thesis is to use the techniques of the compressed sensing, in particular replacing the standard least squares problem of data fitting with the problem of minimizing the 1-norm of the residuals, and using as regularization term the Total Variation (TV). We tested two different algorithms: a new alternating minimization algorithm (ADM), and a version of the more standard scaled projected gradient algorithm (SGP) that involves the 1-norm. We perform some experiments and analyse the performance of the two methods comparing relative errors, iterations number, times and the qualities of the reconstructed images. In conclusion we noticed that the use of the 1-norm and the Total Variation are valid tools in the formulation of the minimization problem for the image reconstruction resulting from Digital Tomosynthesis and the new algorithm ADM has reached a relative error comparable to a version of the classic algorithm SGP and proved best in speed and in the early appearance of the structures representing the masses.

Microwave breast imaging reconstruction

In this thesis I analyzed the microwave tomography method to recognize breast can- cer. I study how identify the dielectric permittivity, the Helmoltz equation parameter used to model the real physic problem. Through a non linear least squares method I solve a problem of parameters identification; I show the theoric approach and the devel- opment to reach the results. I use the Levenberg-Marquardt algorithm, applied on COMSOL software to multiphysic models; so I do numerical proofs on semplified test problems compared to the specific real problem to solve.

Body mass index, hormone replacement therapy, and endometrial cancer risk: a meta-analysis

Background: Body mass index (BMI) is a risk factor for endometrial cancer. We quantified the risk and investigated whether the association differed by use of hormone replacement therapy (HRT), menopausal status, and histologic type. Methods: We searched MEDLINE and EMBASE (1966 to December 2009) to identify prospective studies of BMI and incident endometrial cancer. We did random-effects meta-analyses, meta-regressions, and generalized least square regressions for trend estimations assuming linear, and piecewise linear, relationships. Results: Twenty-four studies (17,710 cases) were analyzed; 9 studies contributed to analyses by HRT, menopausal status, or histologic type, all published since 2003. In the linear model, the overall risk ratio (RR) per 5 kg/m2 increase in BMI was 1.60 (95% CI, 1.52–1.68), P < 0.0001. In the piecewise model, RRs compared with a normal BMI were 1.22 (1.19–1.24), 2.09 (1.94–2.26), 4.36 (3.75–5.10), and 9.11 (7.26–11.51) for BMIs of 27, 32, 37, and 42 kg/m2, respectively. The association was stronger in never HRT users than in ever users: RRs were 1.90 (1.57–2.31) and 1.18 (95% CI, 1.06–1.31) with P for interaction ¼ 0.003. In the piecewise model, the RR in never users was 20.70 (8.28–51.84) at BMI 42 kg/m2, compared with never users at normal BMI. The association was not affected by menopausal status (P ¼ 0.34) or histologic type (P ¼ 0.26). Conclusions: HRT use modifies the BMI-endometrial cancer risk association. Impact: These findings support the hypothesis that hyperestrogenia is an important mechanism underlying the BMI-endometrial cancer association, whilst the presence of residual risk in HRT users points to the role of additional systems. Cancer Epidemiol Biomarkers Prev; 19(12); 3119–30.

Morphological integration between the cranial base and the face in children and adults

The primary aim of the present study was to assess morphological covariation between the face and the basicranium (midline and lateral), and to evaluate patterns of integration at two specific developmental stages. A group of 71 children (6-10 years) was compared with a group of 71 adults (20-35 years). Lateral cephalometric radiographs were digitized and a total of 28 landmarks were placed on three areas; the midline cranial base, the lateral cranial base and the face. Geometric morphometric methods were applied and partial least squares analysis was used to evaluate correlation between the three shape blocks. Morphological integration was tested both with and without removing the effect of allometry. In children, mainly the midline and, to a lesser extent, the lateral cranial base were moderately correlated to the face. In adults, the correlation between the face and the midline cranial base, which ceases development earlier than the lateral base, was reduced. However, the lateral cranial base retained and even strengthened its correlation to the face. This suggests that the duration of common developmental timing is an important factor that influences integration between craniofacial structures. However, despite the apparent switch of primary roles between the cranial bases during development, the patterns of integration remained stable, thereby supporting the role of genetics over function in the establishment and development of craniofacial shape.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

The Incumbent Spending Puzzle

Objective This article seeks to explain the puzzle of why incumbents spend so much on campaigns despite most research finding that their spending has almost no effect on voters. Methods The article uses ordinary least squares, instrumental variables, and fixed-effects regression to estimate the impact of incumbent spending on election outcomes. The estimation includes an interaction term between incumbent and challenger spending to allow the effect of incumbent spending to depend on the level of challenger spending. Results The estimation provides strong evidence that spending by the incumbent has a larger positive impact on votes received the more money the challenger spends. Conclusion Campaign spending by incumbents is most valuable in the races where the incumbent faces a serious challenge. Raising large sums of money to be used in close races is thus a rational choice by incumbents.

Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer

Over the recent years chirped-pulse, Fourier-transform microwave (CP-FTMW) spectrometers have chan- ged the scope of rotational spectroscopy. The broad frequency and large dynamic range make possible structural determinations in molecular systems of increasingly larger size from measurements of heavy atom (13C, 15N, 18O) isotopes recorded in natural abundance in the same spectrum as that of the parent isotopic species. The design of a broadband spectrometer operating in the 2–8 GHz frequency range with further improvements in sensitivity is presented. The current CP-FTMW spectrometer performance is benchmarked in the analyses of the rotational spectrum of the water heptamer, (H2O)7, in both 2– 8 GHz and 6–18 GHz frequency ranges. Two isomers of the water heptamer have been observed in a pulsed supersonic molecular expansion. High level ab initio structural searches were performed to pro- vide plausible low-energy candidates which were directly compared with accurate structures provided from broadband rotational spectra. The full substitution structure of the most stable species has been obtained through the analysis of all possible singly-substituted isotopologues (H218O and HDO), and a least-squares rm(1) geometry of the oxygen framework determined from 16 different isotopic species compares with the calculated O–O equilibrium distances at the 0.01 Å level.

Broadband Fourier transform rotational spectroscopy for structure determination: The water heptamer

Over the recent years chirped-pulse, Fourier-transform microwave (CP-FTMW) spectrometers have changed the scope of rotational spectroscopy. The broad frequency and large dynamic range make possible structural determinations in molecular systems of increasingly larger size from measurements of heavy atom (C-13, N-15, O-18) isotopes recorded in natural abundance in the same spectrum as that of the parent isotopic species. The design of a broadband spectrometer operating in the 2-8 GHz frequency range with further improvements in sensitivity is presented. The current CP-FTMW spectrometer performance is benchmarked in the analyses of the rotational spectrum of the water heptamer, (H2O)(7), in both 2-8 GHz and 6-18 GHz frequency ranges. Two isomers of the water heptamer have been observed in a pulsed supersonic molecular expansion. High level ab initio structural searches were performed to provide plausible low-energy candidates which were directly compared with accurate structures provided from broadband rotational spectra. The full substitution structure of the most stable species has been obtained through the analysis of all possible singly-substituted isotopologues ((H2O)-O-18 and HDO), and a least-squares r(m)((1)) geometry of the oxygen framework determined from 16 different isotopic species compares with the calculated O-O equilibrium distances at the 0.01 angstrom level. (C) 2013 Elsevier B.V. All rights reserved.

Exploring High-resolution Magic Angle Spinning (HR-MAS) NMR Spectroscopy for Metabonomic Analysis of Apples

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

The Effects of Interstate Speed Limit Increases: Fatality Rates and Traffic Diversion Versus Speed Spillover

This thesis examines two panel data sets of 48 states from 1981 to 2009 and utilizes ordinary least squares (OLS) and fixed effects models to explore the relationship between rural Interstate speed limits and fatality rates and whether rural Interstate speed limits affect non-Interstate safety. Models provide evidence that rural Interstate speed limits higher than 55 MPH lead to higher fatality rates on rural Interstates though this effect is somewhat tempered by reductions in fatality rates for roads other than rural Interstates. These results provide some but not unanimous support for the traffic diversion hypothesis that rural Interstate speed limit increases lead to decreases in fatality rates of other roads. To the author’s knowledge, this paper is the first econometric study to differentiate between the effects of 70 MPH speed limits and speed limits above 70 MPH on fatality rates using a multi-state data set. Considering both rural Interstates and other roads, rural Interstate speed limit increases above 55 MPH are responsible for 39,700 net fatalities, 4.1 percent of total fatalities from 1987, the year limits were first raised, to 2009.

Vibrational Relaxation of 13CO2(v2) by Atomic Oxygen

Carbon dioxide (CO2) has been of recent interest due to the issue of greenhouse cooling in the upper atmosphere by species such as CO2 and NO. In the Earth’s upper atmosphere, between altitudes of 75 and 110 km, a collisional energy exchange occurs between CO2 and atomic oxygen, which promotes a population of ground state CO2 to the bend excited state. The relaxation of CO2 following this excitation is characterized by spontaneous emission of 15-μm. Most of this energy is emitted away from Earth. Due to the low density in the upper atmosphere, most of this energy is not reabsorbed and thus escapes into space, leading to a local cooling effect in the upper atmosphere. To determine the efficiency of the CO2- O atom collisional energy exchange, transient diode laser absorption spectroscopy was used to monitor the population of the first vibrationally excited state, 13CO2(0110) or ν2, as a function of time. The rate coefficient, kO(ν2), for the vibrational relaxation 13CO2 (ν2)-O was determined by fitting laboratory measurements using a home-written linear least squares algorithm. The rate coefficient, kO(ν2), of the vibrational relaxation of 13CO2(ν2), by atomic oxygen at room temperature was determined to be (1.6 ± 0.3 x 10-12 cm3 s-1), which is within the uncertainty of the rate coefficient previously found in this group for 12CO2(ν2) relaxation. The cold temperature kO(ν2) values were determined to be: (2.1 ± 0.8) x 10-12 cm3 s-1 at Tfinal = 274 K, (1.8 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 239 K, (2 ± 1) x 10-12 cm3 s-1 at Tfinal = 208 K, and (1.7 ± 0.3) x 10-12 cm3 s-1 at Tfinal = 186 K. These data did not show a definitive negative temperature dependence comparable to that found for 12CO2 previously.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.