21,848 research outputs found
An Integrated Object Model and Method Framework for Subject-Centric e-Research Applications
A framework that integrates an object model, research methods (workflows), the capture of experimental data sets and the provenance of those data sets for subject-centric research is presented. The design of the Framework object model draws on and extends pre-existing object models in the public domain. In particular the Framework tracks the state and life cycle of a subject during an experimental method, provides for reusable subjects, primary, derived and recursive data sets of arbitrary content types, and defines a user-friendly and practical scheme for citably identifying information in a distributed environment. The Framework is currently used to manage neuroscience Magnetic Resonance and microscopy imaging data sets in both clinical and basic neuroscience research environments. The Framework facilitates multi-disciplinary and collaborative subject-based research, and extends earlier object models used in the research imaging domain. Whilst the Framework has been explicitly validated for neuroimaging research applications, it has broader application to other fields of subject-centric research
ImageJ2: ImageJ for the next generation of scientific image data
ImageJ is an image analysis program extensively used in the biological
sciences and beyond. Due to its ease of use, recordable macro language, and
extensible plug-in architecture, ImageJ enjoys contributions from
non-programmers, amateur programmers, and professional developers alike.
Enabling such a diversity of contributors has resulted in a large community
that spans the biological and physical sciences. However, a rapidly growing
user base, diverging plugin suites, and technical limitations have revealed a
clear need for a concerted software engineering effort to support emerging
imaging paradigms, to ensure the software's ability to handle the requirements
of modern science. Due to these new and emerging challenges in scientific
imaging, ImageJ is at a critical development crossroads.
We present ImageJ2, a total redesign of ImageJ offering a host of new
functionality. It separates concerns, fully decoupling the data model from the
user interface. It emphasizes integration with external applications to
maximize interoperability. Its robust new plugin framework allows everything
from image formats, to scripting languages, to visualization to be extended by
the community. The redesigned data model supports arbitrarily large,
N-dimensional datasets, which are increasingly common in modern image
acquisition. Despite the scope of these changes, backwards compatibility is
maintained such that this new functionality can be seamlessly integrated with
the classic ImageJ interface, allowing users and developers to migrate to these
new methods at their own pace. ImageJ2 provides a framework engineered for
flexibility, intended to support these requirements as well as accommodate
future needs
SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem
The quantitative analysis of 3D confocal microscopy images of the shoot
apical meristem helps understanding the growth process of some plants. Cell
segmentation in these images is crucial for computational plant analysis and
many automated methods have been proposed. However, variations in signal
intensity across the image mitigate the effectiveness of those approaches with
no easy way for user correction. We propose a web-based collaborative 3D image
segmentation application, SEGMENT3D, to leverage automatic segmentation
results. The image is divided into 3D tiles that can be either segmented
interactively from scratch or corrected from a pre-existing segmentation.
Individual segmentation results per tile are then automatically merged via
consensus analysis and then stitched to complete the segmentation for the
entire image stack. SEGMENT3D is a comprehensive application that can be
applied to other 3D imaging modalities and general objects. It also provides an
easy way to create supervised data to advance segmentation using machine
learning models
A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages
Loyek C, Kƶlling J, LangenkƤmper D, Niehaus K, Nattkemper TW. A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages. In: Gama J, Bradley E, HollmƩn J, eds. Advances in Intelligent Data Analysis X: 10th International Symposium, IDA 2011, Porto, Portugal, October 29-31, 2011. Proceedings. Lecture Notes in Computer Science. Vol 7014. Berlin, Heidelberg: Springer; 2011: 258-269
Dynamics of colloidal particles in ice
We use X-ray Photon Correlation Spectroscopy (XPCS) to probe the dynamics of colloidal particles in polycrystalline ice. During freezing, the dendritic ice morphology and rejection of particles from the ice created regions of high-particle-density, where some of the colloids were forced into contact and formed disordered aggregates. We find that the particles in these high density regions underwent ballistic motion coupled with both stretched and compressed exponential decays of the intensity autocorrelation function, and that the particlesā characteristic velocity increased with temperature. We explain this behavior in terms of ice grain boundary migration
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