Work featured in the AIM Newsletter

My new collaboration (with Rick Archibald, Anne Gelb, Jan Hesthaven, Rodrigo Platte, Guohui Song and Ed Walsh) was featured in the 2015 American Institute of Mathematics Newsletter.

To quote from the article: …our group is proving how other data inherent to the [MRI] scanning process, such as resonant frequencies and signal decay rates, which are currently used only to provide contrast, can be useful in diagnosing a condition or measuring a response to treatment. Much more information can be extrapolated from the same scan: temperature, blood ow, di usion, structure, and physiology, for example. We’re developing nonconventional image reconstruction techniques to get this information faster and better than has ever been possible before.

Asymptotic sparsity and asymptotic incoherence in practice

Siemens published practical confirmation of some of the ideas introduced in our paper concerning asymptotic sparsity, asymptotic incoherence and resolution dependence and their role in compressed sensing MRI. In particular, they concluded the following:

Current results practically demonstrated that it is possible to break the coherence barrier by increasing the spatial resolution in MR acquisitions. This likewise implies that the full potential of the compressed sensing is unleashed only if asymptotic sparsity and asymptotic incoherence is achieved.

Further information on these ideas, including the practical benefits they lead to, can be found in another recent work of ours here.