Abstract #3835
Unsupervised quality control of prostate MRSI using Non Negative Matrix Factorization
Nassim Tayari 1 , Anca R. Croitor Sava 2 , Diana M. Sima 2 , Sabine Van Huffel 2 , and Arend Heerschap 1
1
Department of Radiology and Nuclear
Medicine, Radboud University Medical Center, Nijmegen,
Netherlands,
2
Department
of Electrical Engineering, Katholieke Universiteit
Leuven, Leuven, Belgium
An automated quality control algorithm plays an
important role in automation of the analysis of MRSI
data of the prostate cancer patients. In this work we
present an automated unsupervised quality control
algorithm for 3D 1H MRSI data sets. The method is based
on feature extraction using Non Negative Matrix
Factorization(NNMF). Consensus decisions of spectral
quality judged by four experts is used as a Gold
Standard for performance evaluation showing that the
algorithm can separate good quality from bad quality
spectra with 90% sensitivity and 90% specificity.
This abstract and the presentation materials are available to members only;
a login is required.
Join Here
