A large body of published work shows that proton (hydrogen 1 [1H]) magnetic resonance
(MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality …

Localized proton magnetic resonance spectroscopy (MRS) of the human brain, first reported
more than 20 years ago, 1–3 is a mature methodology that is used clinically in many medical …

Brain tumor detection depicts a tough job because of its shape, size and appearance
variations. In this manuscript, a deep learning model is deployed to predict input slices as a …

The objective of this study is to investigate the use of pattern classification methods for
distinguishing different types of brain tumors, such as primary gliomas from metastases, and …

This study aimed to identify the optimal radiomic machine-learning classifier for
differentiating glioblastoma (GBM) from solitary brain metastases (MET) preoperatively. Four …

Magnetic resonance imaging (MRI) provides anatomic images and morphometric
characterization of disease, whereas magnetic resonance spectroscopy (MRS) provides …

Abstract Medical Resonance Imaging (MRI) is one of the preferred imaging methods for
brain tumor diagnosis and getting detailed information on tumor type, location, size …

The process of diagnosing brain tumors is very complicated for many reasons, including the
brain's synaptic structure, size, and shape. Machine learning techniques are employed to …

BACKGROUND AND PURPOSE: Treatment-related changes and recurrent tumors often
have overlapping features on conventional MR imaging. The purpose of this study was to …

Objectives To evaluate the diagnostic performance of magnetic resonance (MR) radiomics-
based machine-learning algorithms in differentiating primary central nervous system …