Feasibility of using Gramian angular field for preprocessing MR spectroscopy data in AI classification tasks: Differentiating glioblastoma from lymphoma.

Journal: European journal of radiology
PMID: 39892374

Abstract

OBJECTIVES: To convert 1D spectra into 2D images using the Gramian angular field, to be used as input for convolutional neural network for classification tasks such as glioblastoma versus lymphoma.

Authors

  • Arsany Hakim
    University Institute of Diagnostic and Interventional Neuroradiology, Bern University Hospital, Inselspital (A.H., R.W.), University of Bern, Switzerland.
  • Irena Zubak
    Department of Neurosurgery, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
  • Christina Marx
    University Institute of Diagnostic and Interventional Neuroradiology, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
  • Thomas Rhomberg
    Department of Neurosurgery, Inselspital, University Hospital Bern, Bern, Switzerland. thomas.rhomberg.1@gmail.com.
  • Theoni Maragkou
    Institute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
  • Johannes Slotboom
    DRNN, Institute of Diagnostic and Interventional Neuroradiology/SCAN, University Hospital Bern, Bern, Switzerland.
  • Michael Murek
    Department of Neurosurgery, Inselspital, University Hospital Bern, Bern, Switzerland.

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