2D Mapping of pathological nuclei

The dynamics of genome regions are associated to the functional or dysfunctional behaviour of the human cell. In order to study these dynamics it is necessary to remove perturbations coming from movement and deformation of the nucleus, i.e. the container holding the genome. In literature models have been proposed to cope with the transformations corresponding to nuclear dynamics of healthy cells. However for pathological cells such as cancer cells, the nucleus deforms in an apparently random way, making the use of such models a non trivial task. In this paper we propose a mapping of the cell nucleus which is based on the minimization of telomere motion, i.e. the motion of the very ends of chromosomes

The Rise and Fall of the "Swedish Model"

human development, poverty, empowerment

Computational efficient segmentation of cell nuclei in 2D and 3D fluorescent micrographs

This paper proposes a new segmentation technique developed for the segmentation of cell nuclei in both 2D and 3D fluorescent micrographs. The proposed method can deal with both blurred edges as with touching nuclei. Using a dual scan line algorithm its both memory as computational efficient, making it interesting for the analysis of images coming from high throughput systems or the analysis of 3D microscopic images. Experiments show good results, i.e. recall of over 0.98

Quasar: A Programming Framework for Rapid Prototyping

We present a new programming framework, Quasar, which facilitates GPU programming. Our high-level programming language relieves the developer of all implementation details such that he can focus on the algorithm and the required accuracy. The proposed programming framework consists of a simple high-level programming language, an advanced compiler system, a runtime system and IDE. The Quasar language is a high level scripting language with an easy to learn syntax similar to python and MATLAB. This makes Quasar well suited for fast development and prototyping. A Quasar program is first processed by a front-end compiler that automatically detects serial and parallel loops that could be accelerated by heterogeneous hardware. In a second compilation phase, a number of back-end compilers processes the output of the front-end compiler, thus generating C++, OpenCL or CUDA code. Based on the generated code the runtime system can dynamically switch between CPU and GPU. This automatic scheduling at runtime is done by analyzing the load of all devices, the memory transfer cost and the complexity of the task. This way, the programmer is relieved from complicated implementation issues that are common for programming heterogeneous hardware. We validated the use of Quasar on a number of complex image processing and computer vision algorithms. These programs range from denoising to automated image segmentation applications. Using Quasar we get speed-up factors of 4 to over 60, depending on the application. All results were achieved using an NVIDIA GeForce M750

A computational efficient external energy for active contour segmentation using edge propagation

Active contours or snakes are widely used for segmentation and tracking. We propose a new active contour model, which converges reliably even when the initialization is far from the object of interest. The proposed segmentation technique uses an external energy function where the energy slowly decreases in the vicinity of an edge. This new energy function is calculated using an efficient dual scan line algorithm. The proposed energy function is tested on computational speed, its effect on the convergence speed of the active contour and the segmentation result. The proposed method gets similar segmentation results as the gradient vector flow active contours, but the energy function needs much less time to calculate

A fast external force field for parametric active contour segmentation

Active contours or snakes are widely used for segmentation and tracking. We propose a new active contour model, which converges reliably even when the initialization is far from the object of interest. The proposed segmentation technique uses an external energy function where the energy slowly decreases in the vicinity of an edge. Based on this energy a new external force field is defined. Both energy function and force field are calculated using an efficient dual scan line algorithm. The proposed force field is tested on computational speed, its effect on the convergence speed of the active contour and the segmentation result. The proposed method gets similar segmentation results as the gradient vector flow and vector field convolution active contours, but the force field needs significantly less time to calculate

Mapping of cell nuclei based on contour warping

The dynamics of genome regions are associated to the functional or dysfunctional behaviour of the human cell. In order to study these dynamics it is necessary to remove all perturbations coming from movement and deformation of the nucleus, i.e. the container holding the genome. In literature models have been proposed to cope with the transformations corresponding to nuclear dynamics of healthy cells. However for pathological cells, the nucleus deforms in an apparently random way, making the use of such models a non trivial task. In this paper we propose a mapping of the cell nucleus which is based on the matching of the nuclear contours. The proposed method does not put constraints on the possible shapes nor on the possible deformations, making this method suited for the analysis of pathological nuclei

Embodied cognition through cultural interaction

In this short paper we describe a robotic setup to study the self-organization of conceptualisation and language. What distinguishes this project from others is that we envision a robot with specic cognitive capacities, but without resorting to any pre-programmed representations or conceptualisations. The key to this all is self-organization and enculturation. We report preliminary results on learning motor behaviours through imitation, and sketch how the language plays a pivoting role in constructing world representations

Automatic detection of cell nuclei in fluorescence micrographs

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Robust active contour segmentation with an efficient global optimizer

Active contours or snakes are widely used for segmentation and tracking. Recently a new active contour model was proposed, combining edge and region information. The method has a convex energy function, thus becoming invariant to the initialization of the active contour. This method is promising, but has no regularization term. Therefore segmentation results of this method are highly dependent of the quality of the images. We propose a new active contour model which also uses region and edge information, but which has an extra regularization term. This work provides an efficient optimization scheme based on Split Bregman for the proposed active contour method. It is experimentally shown that the proposed method has significant better results in the presence of noise and clutter