Author:
Gustafson Carl ;
Bug William ;
Nissanov Jonathan

Abstract

Background

Biomedical three-dimensional images sets are becoming ubiquitous, and the atlas canonical providing the framework for spatial analysis. To take full advantage of this 3D image sets, we must be able to present the views 2D display, or the surface of records or 2D cross-sections through the data. Typical of the software is limited to presentations on one of the three orthogonal axes anatomical (coronal, sagittal or horizontal). However, the data sets specifically oriented along the major roads are rare. To make full use of these data, one must reasonably reflect the atlas guidance, which implies resampling in the atlas planes compared with the data set. Traditionally, this requires the atlas and the browser are on the user's desktop, unfortunately, in addition to being monolithic programs, these tools often require substantial resources. In this article, we describe a network capable, and client part of the deal and 3D visualization atlases at off-axis angles, with a score of architecture and development kit to facilitate their integration in complex environments data analysis.

Results

Here, we describe the basic architecture of a client / server 3D visualization system, consisting of a thin client built on a Java Development Kit, and a calculation robust, high-performance server written in ANSI C + +. The client Java components (NetOStat) support arbitrary viewing angle and manage readily available on desktop computers running Mac OS X, Windows XP or Linux in a downloadable Java Application. Using the NeuroTerrain Software Development Kit (SDK NT), Atlas of sophisticated navigation can be added to any application compatible Java requiring as little as 50 lines of Java code glue, which makes it eminently re-useable and more accessible to programmers build more complex, the tools for analyzing biomedical data. The NT-SDK separates interactive GUI components from the server control and monitoring, in order to support the development of non-interactive applications. The application server takes full advantage of the data center of high performance equipment, which can be located together with centrally-located, 3D data repositories, expanding access to the research community through the Internet.

Conclusion

The combination of a server optimized and modular platform independent client offers an ideal environment for 3D visualization complex biomedical data, taking full advantage of high-performance servers to prepare imagery and subsets of metadata for display, as well as the graphical capabilities in Java to actually display the data.

Journal: BMC Bioinformatics Year: 2007 Vol: 8 Issue: 1

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Technorati : 3D data repositories, 3D image, biomedical data, spatial analysis

Author:
Lynch Andy ;
Neal David ;
Kelly John ;
Burtt Glyn ;
Thorne Natalie

Abstract

Background
There are mechanisms, including ozone degradation, which can damage a single channel of two-channel microarray experiments. Analysis therefore often choose between unacceptable inclusion of the poor quality of data or exclusion of certain unpleasant (perhaps a lot of) good quality data as well as the bad. Two of these approaches will be a single channel using some data analysis of all tables, and an analysis of all data, but only about paintings unchanged. In this paper we examine a "combined" approach to the analysis of these experiments affected that uses all the data unchanged.

Results
A simulation experience shows that if a single channel performs an analysis relatively well while the majority of the tables are affected, and the exclusion of affected tables performs relatively well when some tables are affected (as would be expected in both cases) the combined approach performs both off. There are advantages to actively pursue the estimation of the key parameters of the approach, but if they offset the rising cost of computation and complexity of more than just setting parameter to a fixed value n ' is unclear. The inclusion data affected ozone results in poor performance, with a clear purpose in the apparent damage.

Conclusion
It is not necessary to exclude data not allocated, in order to remove those that are damaged. The combined approach discussed here is displayed on the outside make more usual approach, but it seems that if the damage is limited to very few tables, or spreads almost everything, then the benefits will be limited. In other circumstances, however, major improvements in performance can be achieved through the adoption of such an approach.

Journal : BMC Bioinformatics [Year: 2007 ; Volume: 8; Issue: 1]