A Deep Neural Network for Detection of Glioblastomas in Spectroscopic MRI
Erin Beate Bjørkeli1,2, Jonn Terje Geitung1,2, and Morteza Esmaeili1,3
1Department of Diagnostic Imaging, Akershus University Hospital, Oslo, Norway, 2Institue of Clinical Medicine, University of Oslo, Oslo, Norway, 3Department of Electrical Engineering and Computer Science, University of Stavanger, Stavanger, Norway
We have developed a MRSI spectra classifying convolutional neural network (CNN), building on the AUTOMAP model for image and spectra reconstruction. The model was trained to discern between non-water-suppressed spectra from healthy subjects and glioblastoma (GBM) patients. The trained CNN was able to classify the spectra correctly and seemed to recognize the healthy spectra based on the NAA-peak and the GBM based on the choline levels and possibly 2HG, indicating an IDH mutation.
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