Laser Interstitial Thermotherapy is a minimally invasive treatment option in neurosurgery for
intracranial tumors, including recurrent gliomas. The technique employs the thermal ablation …

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

Simple Summary This retrospective study investigates the validity of lateral ventricle opening
during high-grade glioma (HGG) surgery, contributing to the literature by addressing its …

Standard treatment of patients with glioblastoma includes surgical resection of the tumor.
The extent of resection (EOR) achieved during surgery significantly impacts prognosis and is …

ABSTRACT BACKGROUND AND PURPOSE: To develop and evaluate an automated, AI-
based, volumetric brain tumor MRI response assessment algorithm on a large cohort of …

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 …

Objectives The diagnosis and treatment of brain tumors have greatly benefited from
extensive research in traditional radiomics, leading to improved efficiency for clinicians. With …

Purpose Automated glioblastoma segmentation from magnetic resonance imaging is
generally performed on a four-modality input, including T1, contrast T1, T2 and FLAIR. We …

The Brain Tumor Segmentation (BraTS) Challenge has been a main driver of the
development of deep learning (DL) algorithms and provides by far the largest publicly …

Accurately assessing tumor removal is paramount in the management of glioblastoma. We
developed a pipeline using MRI scans and neural networks to segment tumor subregions …