Minimizing bias is critical to adoption and implementation of machine learning (ML) in clinical
practice. Systematic mathematical biases produce consistent and reproducible differences …

Background Missing MRI sequences represent an obstacle in the development and use of
deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing …

There is a growing demand for high-resolution (HR) medical images for both clinical and
research applications. Image quality is inevitably traded off with acquisition time, which in turn …

Introduction Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high
diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects…

Pediatric tumors of the central nervous system are the most common cause of cancer-related
death in children. The five-year survival rate for high-grade gliomas in children is less than …

Purpose To evaluate the feasibility of a standardized protocol for acquisition and analysis of
dynamic contrast material–enhanced (DCE) and dynamic susceptibility contrast (DSC) …

Gliomas are the most common type of primary brain tumors. Although gliomas are relatively
rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years …

Patients with primary central nervous system lymphoma (PCNSL) are treated with high-dose
methotrexate-based chemotherapy, which requires hospitalization and extensive expertise …

Clinical monitoring of metastatic disease to the brain can be a laborious and timeconsuming
process, especially in cases involving multiple metastases when the assessment is …

Background Combining MRI techniques with machine learning methodology is rapidly
gaining attention as a promising method for staging of brain gliomas. This study assesses the …