Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

A Hybrid Model for Multimodal Brain Tumor Segmentation

We present a fully automatic segmentation method for multi-modal brain tumor segmentation. The proposed generative-discriminative hybrid model generates initial tissue probabilities, which are used subsequently for enhancing the classi�cation and spatial regularization. The model has been evaluated on the BRATS2013 training set, which includes multimodal MRI images from patients with high- and low-grade gliomas. Our method is capable of segmenting the image into healthy (GM, WM, CSF) and pathological tissue (necrotic, enhancing and non-enhancing tumor, edema). We achieved state-of-the-art performance (Dice mean values of 0.69 and 0.8 for tumor subcompartments and complete tumor respectively) within a reasonable timeframe (4 to 15 minutes).

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.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

Asymptotic freedom, dimensional transmutation, and an infrared conformal fixed point for the δ-function potential in one-dimensional relativistic quantum mechanics

We consider the Schrödinger equation for a relativistic point particle in an external one-dimensional δ-function potential. Using dimensional regularization, we investigate both bound and scattering states, and we obtain results that are consistent with the abstract mathematical theory of self-adjoint extensions of the pseudodifferential operator H=p2+m2−−−−−−−√. Interestingly, this relatively simple system is asymptotically free. In the massless limit, it undergoes dimensional transmutation and it possesses an infrared conformal fixed point. Thus it can be used to illustrate nontrivial concepts of quantum field theory in the simpler framework of relativistic quantum mechanics.

Interactive Segmentation of MR Images from Brain Tumor Patients

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.

Deliberative and non-deliberative persuasion: Mechanisms of opinion formation in EuroPolis

From a normative vantage point, post-deliberative opinions should be linked to the quality of arguments presented during discussion. Yet, there is a dearth of research testing this claim. Our study makes a first attempt to overcome this deficiency. By analyzing a European deliberative poll on third country migration, we explore whether statements backed by reason affect opinions, which we term deliberative persuasion. We contrast deliberative persuasion to non-deliberative persuasion, whereby we explore whether the most frequently repeated position influences opinions. We find that with regard to regularization of irregular immigrants, deliberative persuasion took place. In the context of European involvement in immigration affairs, however, opinions are driven by the most frequently repeated position rather than by the quality of argumentation.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and 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 approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

The impact of common versus separate estimation of orbit parameters on GRACE gravity field solutions

Gravity field parameters are usually determined from observations of the GRACE satellite mission together with arc-specific parameters in a generalized orbit determination process. When separating the estimation of gravity field parameters from the determination of the satellites’ orbits, correlations between orbit parameters and gravity field coefficients are ignored and the latter parameters are biased towards the a priori force model. We are thus confronted with a kind of hidden regularization. To decipher the underlying mechanisms, the Celestial Mechanics Approach is complemented by tools to modify the impact of the pseudo-stochastic arc-specific parameters on the normal equations level and to efficiently generate ensembles of solutions. By introducing a time variable a priori model and solving for hourly pseudo-stochastic accelerations, a significant reduction of noisy striping in the monthly solutions can be achieved. Setting up more frequent pseudo-stochastic parameters results in a further reduction of the noise, but also in a notable damping of the observed geophysical signals. To quantify the effect of the a priori model on the monthly solutions, the process of fixing the orbit parameters is replaced by an equivalent introduction of special pseudo-observations, i.e., by explicit regularization. The contribution of the thereby introduced a priori information is determined by a contribution analysis. The presented mechanism is valid universally. It may be used to separate any subset of parameters by pseudo-observations of a special design and to quantify the damage imposed on the solution.

Regularizing Image Reconstruction for Gradient-Domain Rendering with Feature Patches

We present a novel algorithm to reconstruct high-quality images from sampled pixels and gradients in gradient-domain rendering. Our approach extends screened Poisson reconstruction by adding additional regularization constraints. Our key idea is to exploit local patches in feature images, which contain per-pixels normals, textures, position, etc., to formulate these constraints. We describe a GPU implementation of our approach that runs on the order of seconds on megapixel images. We demonstrate a significant improvement in image quality over screened Poisson reconstruction under the L1 norm. Because we adapt the regularization constraints to the noise level in the input, our algorithm is consistent and converges to the ground truth.

Trayectorias laborales y habitacionales en hogares de un asentamiento en el área metropolitana del Gran Resistencia (AMGR), Chaco, Argentina

En este artículo abordamos el trabajo y la habitación como dos dimensiones centrales en la reproducción de la vida, enfatizando la realimentación mutua de ambas dimensiones. Caracterizamos las estrategias desplegadas por un conjunto de familias en un asentamiento en proceso de regularización urbana y dominial de la ciudad de Resistencia, capital de la Provincia del Chaco, en el Nordeste argentino. El trabajo de campo se realizó en el marco de una investigación de tesis de Licenciatura en Relaciones Laborales (RRLL) en la Universidad Nacional del Nordeste (UNNE) entre fines del año 2008 y principios del año 2009 y, si bien se basa en un conjunto de entrevistas a residentes de dicho asentamiento, se han puesto en relación un conjunto de indicadores que permiten contextualizar estas visiones subjetivas. La integración a redes de intercambio en diferentes niveles ?comunitario, a través de la integración en una ong o movimiento social, a nivel de las familias y dentro de las unidades domésticas? va construyendo un capital social colectivo que les permite reproducirse socialmente. Este abordaje, tributario de las formulaciones de Bourdieu, nos ha permitido resignificar prácticas, ampliando la noción de trabajo a la de estrategias de reproducción de la vida. Nuestro interés fue describir cómo algunas familias relatan e interpretan sus propias experiencias en relación con sus estrategias de supervivencia. El artículo avanza en una tipologización de las trayectorias estudiadas

Memória e resistência na migraçao para a Amazônia : O caso de Nova Londrina em Ji-Paraná, estado de Rondônia, Brasil

The occupation of Rondônia, from the 1970s, occurred in a disorganized way, since it attracted an amount of migrants which was much bigger than the settling projects could sustain. The aim of this research was to analyze the circumstances in which the district of Nova Londrina was settled, utilizing for this reason a bibliographic survey, as well as the Oral History method. The arrival in Nova Londrina, Ji-Paraná, was highlighted by conflicts between the settlers and the settling company Calama S/A. In spite of the company's violence, the colonists resisted until there was an intervention from INCRA, through a land regularization program. In this context, the Urban Center for Rural Support (NUAR) was implanted, intending to support the agricultural workers

Memória e resistência na migraçao para a Amazônia : O caso de Nova Londrina em Ji-Paraná, estado de Rondônia, Brasil

The occupation of Rondônia, from the 1970s, occurred in a disorganized way, since it attracted an amount of migrants which was much bigger than the settling projects could sustain. The aim of this research was to analyze the circumstances in which the district of Nova Londrina was settled, utilizing for this reason a bibliographic survey, as well as the Oral History method. The arrival in Nova Londrina, Ji-Paraná, was highlighted by conflicts between the settlers and the settling company Calama S/A. In spite of the company's violence, the colonists resisted until there was an intervention from INCRA, through a land regularization program. In this context, the Urban Center for Rural Support (NUAR) was implanted, intending to support the agricultural workers

Trayectorias laborales y habitacionales en hogares de un asentamiento en el área metropolitana del Gran Resistencia (AMGR), Chaco, Argentina

En este artículo abordamos el trabajo y la habitación como dos dimensiones centrales en la reproducción de la vida, enfatizando la realimentación mutua de ambas dimensiones. Caracterizamos las estrategias desplegadas por un conjunto de familias en un asentamiento en proceso de regularización urbana y dominial de la ciudad de Resistencia, capital de la Provincia del Chaco, en el Nordeste argentino. El trabajo de campo se realizó en el marco de una investigación de tesis de Licenciatura en Relaciones Laborales (RRLL) en la Universidad Nacional del Nordeste (UNNE) entre fines del año 2008 y principios del año 2009 y, si bien se basa en un conjunto de entrevistas a residentes de dicho asentamiento, se han puesto en relación un conjunto de indicadores que permiten contextualizar estas visiones subjetivas. La integración a redes de intercambio en diferentes niveles ?comunitario, a través de la integración en una ong o movimiento social, a nivel de las familias y dentro de las unidades domésticas? va construyendo un capital social colectivo que les permite reproducirse socialmente. Este abordaje, tributario de las formulaciones de Bourdieu, nos ha permitido resignificar prácticas, ampliando la noción de trabajo a la de estrategias de reproducción de la vida. Nuestro interés fue describir cómo algunas familias relatan e interpretan sus propias experiencias en relación con sus estrategias de supervivencia. El artículo avanza en una tipologización de las trayectorias estudiadas

Memória e resistência na migraçao para a Amazônia : O caso de Nova Londrina em Ji-Paraná, estado de Rondônia, Brasil

The occupation of Rondônia, from the 1970s, occurred in a disorganized way, since it attracted an amount of migrants which was much bigger than the settling projects could sustain. The aim of this research was to analyze the circumstances in which the district of Nova Londrina was settled, utilizing for this reason a bibliographic survey, as well as the Oral History method. The arrival in Nova Londrina, Ji-Paraná, was highlighted by conflicts between the settlers and the settling company Calama S/A. In spite of the company's violence, the colonists resisted until there was an intervention from INCRA, through a land regularization program. In this context, the Urban Center for Rural Support (NUAR) was implanted, intending to support the agricultural workers