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Abstract #0022

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

Nuno Miguel Pedrosa de Barros1,2, 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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