19,327 research outputs found
How to Extract the Geometry and Topology from Very Large 3D Segmentations
Segmentation is often an essential intermediate step in image analysis. A
volume segmentation characterizes the underlying volume image in terms of
geometric information--segments, faces between segments, curves in which
several faces meet--as well as a topology on these objects. Existing algorithms
encode this information in designated data structures, but require that these
data structures fit entirely in Random Access Memory (RAM). Today, 3D images
with several billion voxels are acquired, e.g. in structural neurobiology.
Since these large volumes can no longer be processed with existing methods, we
present a new algorithm which performs geometry and topology extraction with a
runtime linear in the number of voxels and log-linear in the number of faces
and curves. The parallelizable algorithm proceeds in a block-wise fashion and
constructs a consistent representation of the entire volume image on the hard
drive, making the structure of very large volume segmentations accessible to
image analysis. The parallelized C++ source code, free command line tools and
MATLAB mex files are avilable from
http://hci.iwr.uni-heidelberg.de/software.phpComment: C++ source code, free command line tools and MATLAB mex files are
avilable from http://hci.iwr.uni-heidelberg.de/software.ph
SIRENA: A CAD environment for behavioural modelling and simulation of VLSI cellular neural network chips
This paper presents SIRENA, a CAD environment for the simulation and modelling of mixed-signal VLSI parallel processing chips based on cellular neural networks. SIRENA includes capabilities for: (a) the description of nominal and non-ideal operation of CNN analogue circuitry at the behavioural level; (b) performing realistic simulations of the transient evolution of physical CNNs including deviations due to second-order effects of the hardware; and, (c) evaluating sensitivity figures, and realize noise and Monte Carlo simulations in the time domain. These capabilities portray SIRENA as better suited for CNN chip development than algorithmic simulation packages (such as OpenSimulator, Sesame) or conventional neural networks simulators (RCS, GENESIS, SFINX), which are not oriented to the evaluation of hardware non-idealities. As compared to conventional electrical simulators (such as HSPICE or ELDO-FAS), SIRENA provides easier modelling of the hardware parasitics, a significant reduction in computation time, and similar accuracy levels. Consequently, iteration during the design procedure becomes possible, supporting decision making regarding design strategies and dimensioning. SIRENA has been developed using object-oriented programming techniques in C, and currently runs under the UNIX operating system and X-Windows framework. It employs a dedicated high-level hardware description language: DECEL, fitted to the description of non-idealities arising in CNN hardware. This language has been developed aiming generality, in the sense of making no restrictions on the network models that can be implemented. SIRENA is highly modular and composed of independent tools. This simplifies future expansions and improvements.Comisión Interministerial de Ciencia y Tecnología TIC96-1392-C02-0
3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries
Recent advances in electron microscopy have enabled the imaging of single
cells in 3D at nanometer length scale resolutions. An uncharted frontier for in
silico biology is the ability to simulate cellular processes using these
observed geometries. Enabling such simulations requires watertight meshing of
electron micrograph images into 3D volume meshes, which can then form the basis
of computer simulations of such processes using numerical techniques such as
the Finite Element Method. In this paper, we describe the use of our recently
rewritten mesh processing software, GAMer 2, to bridge the gap between poorly
conditioned meshes generated from segmented micrographs and boundary marked
tetrahedral meshes which are compatible with simulation. We demonstrate the
application of a workflow using GAMer 2 to a series of electron micrographs of
neuronal dendrite morphology explored at three different length scales and show
that the resulting meshes are suitable for finite element simulations. This
work is an important step towards making physical simulations of biological
processes in realistic geometries routine. Innovations in algorithms to
reconstruct and simulate cellular length scale phenomena based on emerging
structural data will enable realistic physical models and advance discovery at
the interface of geometry and cellular processes. We posit that a new frontier
at the intersection of computational technologies and single cell biology is
now open.Comment: 39 pages, 14 figures. High resolution figures and supplemental movies
available upon reques
PPF - A Parallel Particle Filtering Library
We present the parallel particle filtering (PPF) software library, which
enables hybrid shared-memory/distributed-memory parallelization of particle
filtering (PF) algorithms combining the Message Passing Interface (MPI) with
multithreading for multi-level parallelism. The library is implemented in Java
and relies on OpenMPI's Java bindings for inter-process communication. It
includes dynamic load balancing, multi-thread balancing, and several
algorithmic improvements for PF, such as input-space domain decomposition. The
PPF library hides the difficulties of efficient parallel programming of PF
algorithms and provides application developers with the necessary tools for
parallel implementation of PF methods. We demonstrate the capabilities of the
PPF library using two distributed PF algorithms in two scenarios with different
numbers of particles. The PPF library runs a 38 million particle problem,
corresponding to more than 1.86 GB of particle data, on 192 cores with 67%
parallel efficiency. To the best of our knowledge, the PPF library is the first
open-source software that offers a parallel framework for PF applications.Comment: 8 pages, 8 figures; will appear in the proceedings of the IET Data
Fusion & Target Tracking Conference 201
Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review
Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed
The Spine of the Cosmic Web
We present the SpineWeb framework for the topological analysis of the Cosmic
Web and the identification of its walls, filaments and cluster nodes. Based on
the watershed segmentation of the cosmic density field, the SpineWeb method
invokes the local adjacency properties of the boundaries between the watershed
basins to trace the critical points in the density field and the separatrices
defined by them. The separatrices are classified into walls and the spine, the
network of filaments and nodes in the matter distribution. Testing the method
with a heuristic Voronoi model yields outstanding results. Following the
discussion of the test results, we apply the SpineWeb method to a set of
cosmological N-body simulations. The latter illustrates the potential for
studying the structure and dynamics of the Cosmic Web.Comment: Accepted for publication HIGH-RES version:
http://skysrv.pha.jhu.edu/~miguel/SpineWeb
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