Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

Do we need to revise the tripartite subdivision hypothesis of the human subthalamic nucleus (STN)? Response to Alkemade and Forstmann.

Recently in this journal, Alkemade and Forstmann again challenged the evidence for a tripartite organisation to the subthalamic nucleus (STN) (Alkemade & Forstmann 2014). Additionally, they raised specific issues with the earlier published results using 3T MRI to perform in vivo diffusion weighted imaging (DWI) based segmentation of the STN (Lambert et al. 2012). Their comments reveal a common misconception related to the underlying methodologies used, which we clarify in this reply, in addition to highlighting how their current conclusions are synonymous with our original paper. The ongoing debate, instigated by the controversies surrounding STN parcellation, raises important implications for the assumptions and methodologies employed in mapping functional brain anatomy, both in vivo and ex vivo, and reveals a fundamental emergent problem with the current techniques. These issues are reviewed, and potential strategies that could be developed to manage them in the future are discussed further.

The importance of customer's value expectations in customer acquisition

Pro gradu –tutkielman tavoitteena on tutkia asiakasarvoa ja sitä, miten asiakasarvoa voidaan käyttää hyväksi uusasiakashankinnassa. Tällä hetkellä kirjallisuudessa on pinnalla muutos tuotekeskeisyydestä asiakaskeskeiseen näkökulmaan, joka tunnistaa asiakasarvon tärkeyden bisnes suhteissa. Tämä tutkimus osallistuu kyseiseen keskusteluun muodostamalla tavan mitata asiakasarvoa, ja peilaamalla saavutettuja tuloksia uusasiakashankinta prosessiin. Empiirinen tutkimus on toteutettu kahdessa osassa: kvalitatiivisessa sekä kvantitatiivisessa. Ensimmäisessä osassa haastateltiin kahdeksaa potentiaalista asiakasta, minkä jälkeen saadut tulokset vietiin suurempaan skaalaan toteuttamalla kysely suurelle joukolle potentiaalisia asiakkaita. Lopulliset tulokset osoittavat, että asiakasarvon käyttäminen hyväksi uusasiakashankinnassa on erittäin tehokas ja käyttökelpoinen metodi. Asiakasarvoon perustuvat asiakassegmentit mahdollistavat oikeiden arvojen kommunikoinnin oikeille segmenteille. Se antaa yritykselle myös mahdollisuuden valita houkuttelevimmat asiakasryhmät ja vahvistaa asiakaskantaansa.

Processing of zero-derived words in English: an fMRI investigation

Derivational morphological processes allow us to create new words (e.g. punish (V) to noun (N) punishment) from base forms. The number of steps from the basic units to derived words often varies (e.g., nationalitybridge-V) i.e., zero-derivation ( Aronoff, 1980). We compared the processing of one-step (soakingsegmentation.

Gestão de custos utilizando sistema de custeio por atividade-ABC: comparação entre laboratório público e privado de análises clínicas em São Luís-MA.

Neste trabalho, é abordada a importância de se utilizar novas formas (métodos) de rastreamento dos custos indiretos, em instituições pública e privada, demonstrando quanta informação uma administração responsável, na área de saúde, especificamente no setor de laboratórios de análises clínicas, pode visualizar com a utilização do Sistema de Custeio Baseado em Atividade - ABC, em substituição aos sistemas tradicionais de apuração dos custos, tipo o Absorção. Como efeito de trabalho de pesquisa buscou-se estabelecer o método de estudo de casos em duas instituições sendo uma da estrutura de saúde pública de São Luís, e outra da estrutura privada, que também presta os mesmos serviços, todos sob uma mesma remuneração – o SUS. Neste trabalho, permitem-se compará-los e verificar qual a melhor estrutura, seus problemas, limitações para a formação de seus custos. Permite também a análise comparativa entre formatos existentes, tipo o Sistema de Custeio Baseado em atividade – ABC e o sistema de custeio pro absorção. As análises obtidas permitem concluir nestes dois casos que os custos podem ser melhores determinados por uma sistemática de apuração que possibilite desenvolver diferenciais que poderão determinar a sua competitividade e a permanência dos seus serviços. Estas informações permitiriam um melhor desempenho tanto na área pública, quanto o da área privada.

Software zur automatischen Tumordiagnose in der funktionalen MRT der weiblichen Brust

In den westlichen Industrieländern ist das Mammakarzinom der häufigste bösartige Tumor der Frau. Sein weltweiter Anteil an allen Krebserkrankungen der Frau beläuft sich auf etwa 21 %. Inzwischen ist jede neunte Frau bedroht, während ihres Lebens an Brustkrebs zu erkranken. Die alterstandardisierte Mortalitätrate liegt derzeit bei knapp 27 %.rnrnDas Mammakarzinom hat eine relative geringe Wachstumsrate. Die Existenz eines diagnostischen Verfahrens, mit dem alle Mammakarzinome unter 10 mm Durchmesser erkannt und entfernt werden, würden den Tod durch Brustkrebs praktisch beseitigen. Denn die 20-Jahres-Überlebungsrate bei Erkrankung durch initiale Karzinome der Größe 5 bis 10 mm liegt mit über 95 % sehr hoch.rnrnMit der Kontrastmittel gestützten Bildgebung durch die MRT steht eine relativ junge Untersuchungsmethode zur Verfügung, die sensitiv genug zur Erkennung von Karzinomen ab einer Größe von 3 mm Durchmesser ist. Die diagnostische Methodik ist jedoch komplex, fehleranfällig, erfordert eine lange Einarbeitungszeit und somit viel Erfahrung des Radiologen.rnrnEine Computer unterstützte Diagnosesoftware kann die Qualität einer solch komplexen Diagnose erhöhen oder zumindest den Prozess beschleunigen. Das Ziel dieser Arbeit ist die Entwicklung einer vollautomatischen Diagnose Software, die als Zweitmeinungssystem eingesetzt werden kann. Meines Wissens existiert eine solche komplette Software bis heute nicht.rnrnDie Software führt eine Kette von verschiedenen Bildverarbeitungsschritten aus, die dem Vorgehen des Radiologen nachgeahmt wurden. Als Ergebnis wird eine selbstständige Diagnose für jede gefundene Läsion erstellt: Zuerst eleminiert eine 3d Bildregistrierung Bewegungsartefakte als Vorverarbeitungsschritt, um die Bildqualität der nachfolgenden Verarbeitungsschritte zu verbessern. Jedes kontrastanreichernde Objekt wird durch eine regelbasierte Segmentierung mit adaptiven Schwellwerten detektiert. Durch die Berechnung kinetischer und morphologischer Merkmale werden die Eigenschaften der Kontrastmittelaufnahme, Form-, Rand- und Textureeigenschaften für jedes Objekt beschrieben. Abschließend werden basierend auf den erhobenen Featurevektor durch zwei trainierte neuronale Netze jedes Objekt in zusätzliche Funde oder in gut- oder bösartige Läsionen klassifiziert.rnrnDie Leistungsfähigkeit der Software wurde auf Bilddaten von 101 weiblichen Patientinnen getested, die 141 histologisch gesicherte Läsionen enthielten. Die Vorhersage der Gesundheit dieser Läsionen ergab eine Sensitivität von 88 % bei einer Spezifität von 72 %. Diese Werte sind den in der Literatur bekannten Vorhersagen von Expertenradiologen ähnlich. Die Vorhersagen enthielten durchschnittlich 2,5 zusätzliche bösartige Funde pro Patientin, die sich als falsch klassifizierte Artefakte herausstellten.rn

Effects of camera aperture correction on keying and compositing of broadcast video

This contribution discusses the effects of camera aperture correction in broadcast video on colour-based keying. The aperture correction is used to ’sharpen’ an image and is one element that distinguishes the ’TV-look’ from ’film-look’. ’If a very high level of sharpening is applied, as is the case in many TV productions then this significantly shifts the colours around object boundaries with hight contrast. This paper discusses these effects and their impact on keying and describes a simple low-pass filter to compensate for them. Tests with colour-based segmentation algorithms show that the proposed compensation is an effective way of decreasing the keying artefacts on object boundaries.

Symmetric inverse consistent nonlinear registration driven by mutual information.

A nonlinear viscoelastic image registration algorithm based on the demons paradigm and incorporating inverse consistent constraint (ICC) is implemented. An inverse consistent and symmetric cost function using mutual information (MI) as a similarity measure is employed. The cost function also includes regularization of transformation and inverse consistent error (ICE). The uncertainties in balancing various terms in the cost function are avoided by alternatively minimizing the similarity measure, the regularization of the transformation, and the ICE terms. The diffeomorphism of registration for preventing folding and/or tearing in the deformation is achieved by the composition scheme. The quality of image registration is first demonstrated by constructing brain atlas from 20 adult brains (age range 30-60). It is shown that with this registration technique: (1) the Jacobian determinant is positive for all voxels and (2) the average ICE is around 0.004 voxels with a maximum value below 0.1 voxels. Further, the deformation-based segmentation on Internet Brain Segmentation Repository, a publicly available dataset, has yielded high Dice similarity index (DSI) of 94.7% for the cerebellum and 74.7% for the hippocampus, attesting to the quality of our registration method.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Motivational profiles of sporting event volunteers

This article presents an approach for segmenting sporting event volunteers according to differences in their motives. Empirical data were obtained from a sample of 1169 volunteers who registered for the 2014 European Athletics Championships in Zürich. They completed the ‘Volunteer Motivation Scale for International Sporting Events’ (VMS-ISE) questionaire. The validity of the VMS-ISE was replicated by confirmatory factor analysis and the data were cluster analysed to identify distinct motivation-based volunteer profiles. These segmented volunteers on the basis of mutually exclusive motivational characteristics. The external validity of the four motivation-based types (‘community supporters’, ‘material incentive seekers’, ‘social networkers’ and ‘career and personal growth orienteers’) was confirmed with socio-economic, sport-related and volunteer activity-related variables. It is concluded that motivation-based segmentation represents a useful way of gaining a clearer understanding of the patterns underlying the heterogeneity of sporting events volunteers.

Effects of fiscal consolidations in Latin America

We use new data on cyclically adjusted primary balances for Latin America and the Caribbean to estimate e ects of scal consolidations on GDP and some of its components. Identi cation is conducted through a doubly-robust estimation procedure that controls for non-randomness in the "treatment assignment" by inverse probability weighting and impulse responses are generated by local projections. Results suggest output contraction by more than one percent on impact, with economy starting to recover from the second year on. Composition e ects indicate that revenue-based adjustments are way more contractionary than expenditure-based ones. Disentangling efects between demand components, we nd consumption being in general less responsive to consolidations than investment, although nonlinearities associated to initial levels of debt and taxation might play an important role.

Cost of an emerging epidemic: an economic analysis of atrial fibrillation in the UK

Objective: To evaluate the cost of atrial fibrillation (AF) to health and social services in the UK in 1995 and, based on epidemiological trends, to project this estimate to 2000. Design, setting, and main outcome measures: Contemporary estimates of health care activity related to AF were applied to the whole population of the UK on an age and sex specific basis for the year 1995. The activities considered ( and costs calculated) were hospital admissions, outpatient consultations, general practice consultations, and drug treatment ( including the cost of monitoring anticoagulant treatment). By adjusting for the progressive aging of the British population and related increases in hospital admissions, the cost of AF was also projected to the year 2000. Results: There were 534 000 people with AF in the UK during 1995. The direct'' cost of health care for these patients was pound 244 million (similar toE350 million) or 0.62% of total National Health Service ( NHS) expenditure. Hospitalisations and drug prescriptions accounted for 50% and 20% of this expenditure, respectively. Long term nursing home care after hospital admission cost an additional pound46.4 million (similar toE66 million). The direct cost of AF rose to pound459 million (similar toE655 million) in 2000, equivalent to 0.97% of total NHS expenditure based on 1995 figures. Nursing home costs rose to pound111 million (similar toE160 million). Conclusions: AF is an extremely costly public health problem.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.