Abstract #0022

Automatic quality assessment of short and long-TE brain tumour MRSI data using novel Spectral Features

Nuno Miguel Pedrosa de Barros^1,2, Urspeter Knecht¹, Richard McKinley¹, Jonathan Giezendanner¹, Roland Wiest¹, and Johannes Slotboom¹

¹Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland, ²University of Bern, Bern, Switzerland

MRSI-data frequently contains bad-quality spectra which strongly limits its clinical-use. Current clinical practice in our institute is that these bad-quality spectra are filtered out by an MRS-expert, at the expense of long processing times. In this work we present a new method for automatic quality assessment of both long and short-TE MRSI brain tumour data. This method is based upon a novel set of spectral features, and it is as accurate as an expert but considerably faster (3/4 minutes vs 3seconds).

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