With the influx of available multi-modality neuroimaging data, the need to mine large databases for interesting features in a modality neutral way across many brain disorders is of interest. In this paper I present some examples of applying models originating in the computer vision and text mining communities to neuroimaging data which are not tuned for a particular imaging modality and are agnostic to the underlying brain disorder.
['David B. Keator']
Modality neutral techniques for brain image understanding