MRI-based medical image analysis for brain tumor studies is gaining attention in recent
times due to an increased need for efficient and objective evaluation of large amounts of …

Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …

Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding
normal brain tissue beyond the lesion outlines visible in the current medical scans. These …

AI for cancer detection encounters the bottleneck of data scarcity, annotation difficulty, and
low prevalence of early tumors. Tumor synthesis seeks to create artificial tumors in medical …

Automated segmentation of brain glioma plays an active role in diagnosis decision,
progression monitoring and surgery planning. Based on deep neural networks, previous …

Prognostic tumor growth modeling via volumetric medical imaging observations can
potentially lead to better outcomes of tumor treatment management and surgical planning …

Recently, radiogenomics or imaging genomics has emerged as a novel high-throughput
method of associating imaging features with genomic data. Radiogenomics has the potential …

Increased intracranial pressure is the source of most critical symptoms in patients with
glioma, and often the main cause of death. Clinical interventions could benefit from non …

Central nervous system (CNS) tumors come with vastly heterogeneous histologic,
molecular, and radiographic landscapes, rendering their precise characterization …

The quantitative analysis of images acquired in the diagnosis and treatment of patients with
brain tumors has seen a significant rise in the clinical use of computational tools. The …