Thursday, March 14, 2013

Magnetic resonance fingerprinting

Mark Griswold just sent me the following, this is awesome!

Dear Igor,

I thought I would refer you to our new paper that has just been published in Nature. This paper describes a new way of collecting and processing MRI data that was inspired by a lot of the random-imaging work that you have featured at Nuit Blanche over the years. The explanation in the paper is rather simple since it had to be written for a general scientific readership, but I am sure that your audience will be able to make the next logical leaps to see how this could be used down the road. Let me know if you have any questions!

Here's a link to the article:

And to a News and Views review written by Brian Welch:

Thanks for keeping Nuit Blanche going! The huge chunk of my new ideas come from your postings... thanks again!

Dr. Mark Griswold, Ph.D.
Professor of Radiology,
Director of MRI Research
Case Western Reserve University
Thanks Mark, looks like fingerprinting or feature based sensing has a new champion and MRI might not look like the same anymore.

Here is the paper: Magnetic resonance fingerprinting by Dan Ma, Vikas Gulani, Nicole Seiberlich, Kecheng Liu,, Jeffrey L. Sunshine, Jeffrey L. Duerk and Mark A. Griswold . The abstract reads:
Magnetic resonance is an exceptionally powerful and versatile measurement technique. The basic structure of a magnetic resonance experiment has remained largely unchanged for almost 50 years, being mainly restricted to the qualitative probing of only a limited set of the properties that can in principle be accessed by this technique. Here we introduce an approach to data acquisition, post-processing and visualization—which we term ‘magnetic resonance fingerprinting’ (MRF)—that permits the simultaneous non-invasive quantification of multiple important properties of a material or tissue. MRF thus provides an alternative way to quantitatively detect and analyse complex changes that can represent physical alterations of a substance or early indicators of disease. MRF can also be used to identify the presence of a specific target material or tissue, which will increase the sensitivity, specificity and speed of a magnetic resonance study, and potentially lead to new diagnostic testing methodologies. When paired with an appropriate pattern-recognition algorithm, MRF inherently suppresses measurement errors and can thus improve measurement accuracy.
Nature is a Romeo yellow Journal (i.e. author cannot archive publisher's version/PDF, but authors can archive pre-prints (ie pre-refereeing)

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