Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and
has been shown to aid the clinical management of several brain diseases. Although most …

Once an MRS dataset has been acquired, several important steps must be taken to obtain
the desired metabolite concentration measures. First, the data must be preprocessed to …

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging
technique that allows for the measurement of brain metabolites that has demonstrated utility …

Purpose To develop a robust method for brain metabolite quantification in proton magnetic
resonance spectroscopy (1H‐MRS) using a convolutional neural network (CNN) that maps …

Purpose To make use of deep learning (DL) methods to detect and remove ghosting artifacts
in clinical magnetic resonance spectra of human brain. Methods Deep learning algorithms …

Purpose Proton MRSI is a noninvasive modality capable of generating volumetric maps of in
vivo tissue metabolism without the need for ionizing radiation or injected contrast agent …

Purpose MRSI has shown great promise in the detection and monitoring of neurologic
pathologies such as tumor. A necessary component of data processing includes the …

The applicability of generative adversarial networks (GANs) capable of unsupervised
anomaly detection (AnoGAN) was investigated in the management of quality of 1 H-MRS …

Purpose While 3D MR spectroscopic imaging (MRSI) provides valuable spatial metabolic
information, one of the hurdles for clinical translation is its interpretation, with voxel-wise …

Purpose To investigate and compare human judgment and machine learning tools for
quality assessment of clinical MR spectra of brain tumors. Methods A very large set of 2574 …