We create three tools using NeuroView to best analyze our research results: CC200 search, SVM coefficients and Connectivity matrix.
This is an initial version of a browser-based neuroimage viewer. The main focus is to develop an embeddable viewer, instead of a standalone desktop software. By doing so, research results can be presented on interactive views, enriching their analysis and interpretation. In our case study, NeuroView facilitates quick evaluation of features for machine learning algorithms, and promotes discussion about them, since the results will inform researchers about their data.
In future work, we aim to directly load Nifti images at client-side and support some AFNI features, such as voxel clustering.
Read the peer-reviewed publication(s):
Craddock, R. C., Bellec, P., Margules, D. S., Nichols, B. N., Pfannmöller, J. P., Badhwar, A., … Cipollini, B. (2016). 2015 Brainhack Proceedings. GigaScience, 5(S1), 1–26. doi:10.1186/s13742-016-0147-0