For patients suffering from brain tumor, prognosis estimation and treatment decisions are
made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the …

Objective Clinical and surgical decisions for glioblastoma patients depend on a tumor
imaging-based evaluation. Artificial Intelligence (AI) can be applied to magnetic resonance …

It is well known how the precise localization of glioblastoma multiforme (GBM) predicts the
direction of tumor spread in the surrounding neuronal structures. The aim of the present …

For patients suffering from central nervous system tumors, prognosis estimation, treatment
decisions, and postoperative assessments are made from the analysis of a set of magnetic …

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed
with glioblastoma. To achieve this, accurate segmentation and classification of residual …

Simple Summary Neurosurgical decisions for patients with glioblastoma depend on visual
inspection of a preoperative MR scan to determine the tumor characteristics. To avoid …

Deep learning (DL) has been applied to glioblastoma (GBM) magnetic resonance imaging
(MRI) assessment for tumor segmentation and inference of molecular, diagnostic, and …

Objective With an increase in the number of imaging examinations and the development of
imaging technology, a small number of glioblastomas (GBMs) are identified by incidental …

Background Glioma is the most common intra-axial tumor, and its location relative to critical
areas of the brain is important for treatment decision-making. Studies often report tumor …

Surgical decision-making for glioblastoma poses significant challenges due to its complexity
and variability. This study investigates the potential of artificial intelligence (AI) tools in …