Use of Remote Surface Based Tools for Visualizing Integrated Brain Imaging Data

We describe a surface-based approach to 3D visualization of integrated neuroimaging data. Our web-enabled software allows researchers to use these visualization tools over the Internet. We present examples of brain imaging studies where such remote surface-based visualization techniques have proven to be quite effective

Brain Visualization in Java3D

BrainJ3D is a cross-platform Java/Java3D software toolkit for processing and visualizing brain imaging data, which 1) contains general purpose tools for reconstructing, mapping and visualizing integrated structural and functional images and 2) leverages Java's Remote Method Invocation to provide both a standalone and a client/server mode

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data

Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine

Lightweight XML-based query, integration and visualization of distributed, multimodality brain imaging data

A need of many neuroimaging researchers is to integrate multimodality brain data that may be stored in separate databases. To address this need we have developed a framework that provides a uniform XML-based query interface across multiple online data sources. The development of this framework is driven by the need to integrate neurosurgical and neuroimaging data related to language. The data sources for the language studies are 1) a web-accessible relational database of neurosurgical cortical stimulation mapping data (CSM) that includes patient-specific 3-D coordinates of each stimulation site mapped to an MRI reconstruction of the patient brain surface; and 2) an XML database of fMRI and structural MRI data and analysis results, created automatically by a batch program we have embedded in SPM. To make these sources available for querying each is wrapped as an XML view embedded in a web service. A top level web application accepts distributed XQueries over the sources, which are dispatched to the underlying web services. Returned results can be displayed as XML, HTML, CSV (Excel format), a 2-D schematic of a parcellated brain, or a 3-D brain visualization. In the latter case the CSM patient-specific coordinates returned by the query are sent to a transformation web-service for conversion to normalized space, after which they are sent to our 3-D visualization program MindSeer, which is accessed via Java WebStart through a generated link. The anatomical distribution of pooled CSM sites can then be visualized using various surfaces derived from brain atlases. As this framework is further developed and generalized we believe it will have appeal for researchers who wish to query, integrate and visualize results across their own databases as well as those of collaborators

Unobtrusive Integration of Data Management With fMRI Analysis

This note describes a software utility, called X-batch which addresses two pressing issues typically faced by functional magnetic resonance imaging (fMRI) neuroimaging laboratories (1) analysis automation and (2) data management. The first issue is addressed by providing a simple batch mode processing tool for the popular SPM software package (http://www.fil.ion. ucl.ac.uk/spm/; Welcome Department of Imaging Neuroscience, London, UK). The second is addressed by transparently recording metadata describing all aspects of the batch job e.g., subject demographics, analysis parameters, locations and names of created files, date and time of analysis, and so on). These metadata are recorded as instances of an extended version of the Protégé-based Experiment Lab Book ontology created by the Dartmouth fMRI Data Center. The resulting instantiated ontology provides a detailed record of all fMRI analyses performed, and as such can be part of larger systems for neuroimaging data management, sharing, and visualization. The X-batch system is in use in our own fMRI research, and is available for download at http://X-batch.sourceforge.net/

Distributed XQuery-based integration and visualization of multimodality data: Application to brain mapping.

This paper addresses the need for relatively small groups of collaborating investigators to integrate distributed and heterogeneous data about the brain. Although various national efforts facilitate large-scale data sharing, these approaches are generally too “heavyweight” for individual or small groups of investigators, with the result that most data sharing among collaborators continues to be ad hoc. Our approach to this problem is to create a “lightweight” distributed query architecture, in which data sources are accessible via web services that accept arbitrary query languages but return XML results. A Distributed XQuery Processor (DXQP) accepts distributed XQueries in which subqueries are shipped to the remote data sources to be executed, with the resulting XML integrated by DXQP. A web-based application called DXBrain accesses DXQP, allowing a user to create, save and execute distributed XQueries, and to view the results in various formats including a 3-D brain visualization. Example results are presented using distributed brain mapping data sources obtained in studies of language organization in the brain, but any other XML source could be included. The advantage of this approach is that it is very easy to add and query a new source, the tradeoff being that the user needs to understand XQuery and the schemata of the underlying sources. For small numbers of known sources this burden is not onerous for a knowledgeable user, leading to the conclusion that the system helps to fill the gap between ad hoc local methods and large scale but complex national data sharing efforts

Web-enabled 3D Multimodality Brain Visualization in Java

MindSeer (formerly BrainJ3D) is designed to meet the needs of current and future users wanting to visualize multimodal 3 and 4 dimensional neuroimaging data. MindSeer runs on Mac, Unix and Windows. Researchers also require fast performance, and should not be expected to convert their data into new formats. Furthermore, there is a pressing need to remotely collaborate and share data - with the world or just with a trusted group of people

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data-4

<p><b>Copyright information:</b></p><p>Taken from "MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data"</p><p>http://www.biomedcentral.com/1471-2105/8/389</p><p>BMC Bioinformatics 2007;8():389-389.</p><p>Published online 15 Oct 2007</p><p>PMCID:PMC2099449.</p><p></p>lices. fMRI (warm colors), and 2 related source localized EEG volumes (green and magenta) are simultaneously shown superimposed on the structural MRI. Right. The same data shown in the Surface viewport. In this case the fMRI is shown as red iso-surfaces and the EEG data are shown with a cutaway view

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data-2

<p><b>Copyright information:</b></p><p>Taken from "MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data"</p><p>http://www.biomedcentral.com/1471-2105/8/389</p><p>BMC Bioinformatics 2007;8():389-389.</p><p>Published online 15 Oct 2007</p><p>PMCID:PMC2099449.</p><p></p>nt the locations of temporal lobe CSM sites in which male patients made semantic (as opposed to syntactic) language errors in response to cortical stimulation. The locations, sizes and colors of the spheres were passed to MindSeer via the information system

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data-3

<p><b>Copyright information:</b></p><p>Taken from "MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data"</p><p>http://www.biomedcentral.com/1471-2105/8/389</p><p>BMC Bioinformatics 2007;8():389-389.</p><p>Published online 15 Oct 2007</p><p>PMCID:PMC2099449.</p><p></p