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

Fast unsupervised multiresolution color image segmentation using adaptive gradient thresholding and progressive region growing

In this thesis, we propose a fast unsupervised multiresolution color image segmentation algorithm which takes advantage of gradient information in an adaptive and progressive framework. This gradient-based segmentation method is initialized by a vector gradient calculation on the full resolution input image in the CIE L*a*b* color space. The resultant edge map is used to adaptively generate thresholds for classifying regions of varying gradient densities at different levels of the input image pyramid, obtained through a dyadic wavelet decomposition scheme. At each level, the classification obtained by a progressively thresholded growth procedure is combined with an entropy-based texture model in a statistical merging procedure to obtain an interim segmentation. Utilizing an association of a gradient quantized confidence map and non-linear spatial filtering techniques, regions of high confidence are passed from one level to another until the full resolution segmentation is achieved. Evaluation of our results on several hundred images using the Normalized Probabilistic Rand (NPR) Index shows that our algorithm outperforms state-of the art segmentation techniques and is much more computationally efficient than its single scale counterpart, with comparable segmentation quality

Robust Digital Holography For Ultracold Atom Trapping

We have formulated and experimentally demonstrated an improved algorithm for design of arbitrary two-dimensional holographic traps for ultracold atoms. Our method builds on the best previously available algorithm, MRAF, and improves on it in two ways. First, it allows for creation of holographic atom traps with a well defined background potential. Second, we experimentally show that for creating trapping potentials free of fringing artifacts it is important to go beyond the Fourier approximation in modelling light propagation. To this end, we incorporate full Helmholtz propagation into our calculations.Comment: 7 pages, 4 figure

Phase-space structures II: Hierarchical Structure Finder

A new multi-dimensional Hierarchical Structure Finder (HSF) to study the phase-space structure of dark matter in N-body cosmological simulations is presented. The algorithm depends mainly on two parameters, which control the level of connectivity of the detected structures and their significance compared to Poisson noise. By working in 6D phase-space, where contrasts are much more pronounced than in 3D position space, our HSF algorithm is capable of detecting subhaloes including their tidal tails, and can recognise other phase-space structures such as pure streams and candidate caustics. If an additional unbinding criterion is added, the algorithm can be used as a self-consistent halo and subhalo finder. As a test, we apply it to a large halo of the Millennium Simulation, where 19 % of the halo mass are found to belong to bound substructures, which is more than what is detected with conventional 3D substructure finders, and an additional 23-36 % of the total mass belongs to unbound HSF structures. The distribution of identified phase-space density peaks is clearly bimodal: high peaks are dominated by the bound structures and low peaks belong mostly to tidal streams. In order to better understand what HSF provides, we examine the time evolution of structures, based on the merger tree history. Bound structures typically make only up to 6 orbits inside the main halo. Still, HSF can identify at the present time at least 80 % of the original content of structures with a redshift of infall as high as z <= 0.3, which illustrates the significant power of this tool to perform dynamical analyses in phase-space.Comment: Submitted to MNRAS, 24 pages, 18 figure

Tracking multiple objects using intensity-GVF snakes

Active contours or snakes are widely used for segmentation and tracking. Multiple object tracking remains a difficult task, characterised by a trade off between increasing the capturing range of edges of the object of interest, and decreasing the capturing range of other edges. We propose a new external force field which is calculated for every object independently. This new force field uses prior knowledge about the intensity of the object of interest. Using this extra information, this new force field helps in discriminating between edges of interest and other objects. For this new force field, the expected intensity of an object must be estimated. We propose a technique which calculates this estimation out of the image