Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Objective To determine the feasibility and biologic correlations of dynamic susceptibility
contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from …

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy
more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction …

BACKGROUND AND PURPOSE: Recent advances in machine learning have enabled
image-based prediction of local tissue pathology in gliomas, but the clinical usefulness of …

Objective Epigenetic tumor features are getting into focus as prognostic markers in
glioblastoma. Whether intra-tumoral heterogeneity in these epigenetic characteristics may …

Deep learning (DL) is poised to redefine the way medical images are processed and
analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are …

The current work investigates the effect of humid conditions on the glass cover temperature
distribution of the parabolic trough solar collector system. For the aforementioned work, a …

We describe a preliminary effort to model the growth and progression of glioblastoma
multiforme, an aggressive form of primary brain cancer, in patients undergoing treatment for …

Transmembrane water exchange (TWE) including transcytolemmal water exchange and
transvascular water exchange is involved in many in vivo measurements and makes …

Reaction-diffusion models have been proposed for decades to capture the growth of
gliomas. Nevertheless, these models require an initial condition: the tumor cell density …