Geometric distortion correction in EPI at ultra high field

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

A comparative analysis of Cobb-Douglas model with additive and multiplicative error

This paper dis cusses the fitting of a Cobb-Doug las response curve Yi = αXβi, with additive error, Yi = αXβi + e i, instead of the usual multiplicative error Yi = αXβi (1 + e i). The estimation of the parameters A and B is discussed. An example is given with use of both types of error.

Stability and error analysis for a numerical scheme to approximate elastic flow

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Univ., Dissertation, 2015

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.

On the density distribution across space: a probabilistic approach

This paper aims at providing a Bayesian parametric framework to tackle the accessibility problem across space in urban theory. Adopting continuous variables in a probabilistic setting we are able to associate with the distribution density to the Kendall's tau index and replicate the general issues related to the role of proximity in a more general context. In addition, by referring to the Beta and Gamma distribution, we are able to introduce a differentiation feature in each spatial unit without incurring in any a-priori definition of territorial units. We are also providing an empirical application of our theoretical setting to study the density distribution of the population across Massachusetts.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Outcomes and reoperations after total correction of complete atrio-ventricular septal defect

BACKGROUND: Surgical correction of complete atrio-ventricular septal defect (AVSD) achieves satisfactory results with low morbidity and mortality, but may require reoperation. Our recent operative results at mid-term were followed-up. METHODS: From June 2000 to December 2007, 81 patients (Down syndrome; n=60), median age 4.0 months (range 0.7-118.6) and weight 4.7kg (range 2.2-33), underwent complete AVSD correction. Patch closure for the ventricular septal defect (VSD; n=69) and atrial septal defect (ASD; n=42) was performed with left atrio-ventricular valve (LAVV) cleft closure (n=76) and right atrio-ventricular valve (RAVV) repair (n=57). Mortality, morbidity, and indications for reoperation were retrospectively studied; the end point 'time to reoperation' was analyzed using Kaplan-Meier curves. Follow-up was complete except in two patients and spanned a median of 28 months (range 0.4-6.1 years). RESULTS: In-hospital mortality was 3.7% (n=3) and one late death occurred. Reoperation was required in 7/79 patients (8.9%) for LAVV insufficiency (n=4), for a residual ASD (n=1), for right atrio-ventricular valve insufficiency (n=1), and for subaortic stenosis (n=1). At last follow-up, no or only mild LAVV and RAVV insufficiency was present in 81.3% and 92.1% of patients, respectively, and 2/3 of patients were medication-free. Risk factors for reoperation were younger age (<3 months; p=0.001) and lower weight (<4kg; p=0.003), and a trend towards less and later reoperations in Down syndrome (p<0.2). CONCLUSIONS: Surgical correction of AVSD can be achieved with low mortality and need for reoperation, regardless of Down syndrome or not. Immediate postoperative moderate or more residual atrio-ventricular valve insufficiency will eventually require a reoperation, and could be anticipated in patients younger than 3 months and weighing <4kg.

A mixed splicing procedure for economic time series

This note develops a flexible methodology for splicing economic time series that avoids the extreme assumptions implicit in the procedures most commonly used in the literature. It allows the user to split the required correction to the older of the series being linked between its levels and growth rates on the basis what he knows or conjectures about the persistence of the factors that account for the discrepancy between the two series that emerges at their linking point. The time profile of the correction is derived from the assumption that the error in the older series reflects the inadequate coverage of emerging sectors or activities that grow faster than the aggregate.

DNA evidence, probabilistic evaluation and collaborative tests.

Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

Significant correction of disease after postnatal administration of recombinant ectodysplasin A in canine X-linked ectodermal dysplasia.

Patients with defective ectodysplasin A (EDA) are affected by X-linked hypohidrotic ectodermal dysplasia (XLHED), a condition characterized by sparse hair, inability to sweat, decreased lacrimation, frequent pulmonary infections, and missing and malformed teeth. The canine model of XLHED was used to study the developmental impact of EDA on secondary dentition, since dogs have an entirely brachyodont, diphyodont dentition similar to that in humans, as opposed to mice, which have only permanent teeth (monophyodont dentition), some of which are very different (aradicular hypsodont) than brachyodont human teeth. Also, clinical signs in humans and dogs with XLHED are virtually identical, whereas several are missing in the murine equivalent. In our model, the genetically missing EDA was compensated for by postnatal intravenous administration of soluble recombinant EDA. Untreated XLHED dogs have an incomplete set of conically shaped teeth similar to those seen in human patients with XLHED. After treatment with EDA, significant normalization of adult teeth was achieved in four of five XLHED dogs. Moreover, treatment restored normal lacrimation and resistance to eye and airway infections and improved sweating ability. These results not only provide proof of concept for a potential treatment of this orphan disease but also demonstrate an essential role of EDA in the development of secondary dentition.

The size of the underground economy in Germany: A correction of the record and new evidence from the Modified-Cash-deposit-Ratio approach

Based on the Ahumada et al. (2007, Review of Income and Wealth) critique we revise existing estimates of the size of the German underground economy. Among other things, it turns out that most of these estimates are untenable and that the tax pressure induced size of the German underground economy may be much lower than previously thought. To this extent, German policy and law makers have been misguided during the last three decades. Therefore, we introduce the Modified-Cash-Deposit-Ratio (MCDR) approach, which is not subject to the recent critique and apply it to Germany for the period 1960 to 2008. JEL: O17, Q41, C22, Keywords: underground economy, shadow economy, cash-depositratio, currency demand approach, MIMIC approach

Desarrollo de un sistema integrado de navegación inercial: interfície IMU + FPGA

Els sistemes automatitzats que requereixen d’un control d’estabilitat o moviment es poden trobar cada cop en més àmbits. Aplicacions UAV o de posicionament global són les més comunes per aquest tipus de sistemes, degut a que necessiten d’un control de moviment molt precís. Per a dur a terme aquest procés s’utilitzen unitats de mesura inercial, que mitjançant acceleròmetres i giroscopis degudament posicionats, a més a més d’una correcció del possible error que puguin introduir aquests últims, proporcionen una acceleració i una velocitat angular de les quals es pot extreure el camí efectuat per aquestes unitats. La IMU, combinada amb un GPS i mitjançant un filtre de Kalman, proporcionen una major exactitud , a més d’un punt de partida (proporcionat per el GPS), un recorregut representable en un mapa y, en el cas de perdre la senyal GPS, poder seguir adquirint dades de la IMU. Aquestes dades poden ser recollides i processades per una FPGA, que a la vegada podem sincronitzar amb una PDA per a que l’usuari pugui veure representat el moviment del sistema. Aquest treball es centra en el funcionament de la IMU i l’adquisició de dades amb la FPGA. També introdueix el filtre de Kalman per a la correcció de l’error dels sensors.

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.