Invizian© blends gigabytes of brain images, meta-data information, and annotations from multiple sources into a seamless, immersive, visually rich experience. Our team is working to aggregate neuroscientific imaging data gathered from leading research centers and permit multi-scale renderings available through a single, cohesive desktop portal.

Neuroimaging data repositories, like the LONI Integrated Data Archive (IDA), contain the raw neuroimaging data from individual subjects who were scanned using MRI and other imaging technology. Ordinarily, such archives can be difficult to explore and one must have some idea of what one is looking for in order to get started. Invizian© will present the data to the user using a three dimensional coordinate system that groups like-data together.

It is possible to compare neuroimaging data sets against one another and determine “how far apart” they are. A coordinate system relates the distance in space proportionately to the similarities between data set variables. These variables can be determined by the user and may include subject physical attributes, geometric surface metrics, cortical thickness, etc. For example, like the sun to our solar system, Invizian© can use a celestial coordinate system model. This model allows the user to start at a common point of reference. Applied to brain data, a known neuroanatomical atlas can be used as the point of reference at the origin for all other brains so that the units of measure between brain locations have ‘real’ meaning to the user. The celestial coordinate system thus organizes the data set into visually manageable, understandable, and relevant spatial framework.

In order to compute the variables between the massive data sets, our team utilizes purpose-built processing workflows, using the LONI Pipeline that are run on the LONI computational grid. We are then able to systematically characterize the geometric properties of brain regional parcellations, store these measurements, and computationally assess pair-wise regional “distances” between brains, and decompose the resulting similarity matrix using multivariate models. This gives rise to the concept of “meta-spaces” – derived coordinate systems that relate content based upon its (dis) similarity.

A collection of robust data processing meta-workflows are being designed to automate workflow-based decomposition of individual MR volumes of brain anatomy into comparable neuroanatomical shape elements. An efficient architecture is being developed for containing derived shape measurements as well as efficient computational means for assessing regional differences in brain shape elements. These meta-workflows utilize such openly available software tools as FSL, AIR, MNI, as well as LONI-based software tools.

For more details and to stay updated on the program development, follow the Invizian© developer’s blog.

The Invizian© software has been developed by John Darrell Van Horn, Sumiko Abe, Ian Bowman, and Shantanu Joshi. The software is provided free for use for non-commercial, research-only use under the LONI Software License.

© 2015 Invizian. All Rights Reserved.

For more details and to stay updated on the program development, follow us the NITRC Website also check us out on BitBucket (account required).

The software is available to download for your Windows (invizian_1.6.6_win64_setup) or Linux (invizian_1.4.6-1_amd64.deb) computer, free of charge. Send a note to us here at INVIZIAN with your email address to get access to an example set of data.