The high-throughput extraction of quantitative information from medical images, known as
radiomics, has grown in interest due to the current necessity to quantitatively characterize …

Motivation Brain or central nervous system cancer is the tenth leading cause of death in men
and women. Even though brain tumour is not considered as the primary cause of mortality …

Background Although biopsy is the gold standard for tumour grading, being invasive, this
procedure also proves fatal to the brain. Thus, non-invasive methods for brain tumour …

Abstract Introduction Brain metastases (BMs) are common in lung cancer (LC) and are
associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the …

Background The aim of this study was to investigate the potential of combined textural
feature analysis of contrast-enhanced MRI (CE-MRI) and static O-(2-[18 F] fluoroethyl)-L …

Current deep learning-assisted brain tumor classification models sustain inductive bias and
parameter dependency problems for extracting texture-based image information. Thereby …

Background: Brain metastases are associated with poor survival. Molecular genetic testing
informs on targeted therapy and survival. The purpose of this study was to perform a MR …

Purpose More and more small brain metastases (BMs) in asymptomatic patients can be
detected even prior to their primary lung cancer with the development of MRI. The aim of this …

Lung cancer metastases comprise most of all brain metastases in adults and most brain
metastases are diagnosed by magnetic resonance (MR) scans. The purpose of this study …

Purpose Textural measures have been widely explored as imaging biomarkers in cancer.
However, their robustness under dynamic range and spatial resolution changes in brain 3D …