BACKGROUND AND PURPOSE: Identification of new MS lesions on longitudinal MR
imaging by human readers is time-consuming and prone to error. Our objective was to …

Introduction Multiple sclerosis (MS) is a serious disease typically occurring in the brain
whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging …

We developed a robust automated algorithm called statistical detection of changes for
detecting morphologic changes of multiple sclerosis lesions between 2 T2-weighted FLAIR …

BACKGROUND AND PURPOSE: MR imaging is the key examination in the follow-up of
patients with MS, by identification of new high-signal T2 brain lesions. However, identifying …

The goal of this study was to create an algorithm which would quantitatively compare serial
magnetic resonance imaging studies of brain-tumor patients. A novel algorithm and a …

BACKGROUND AND PURPOSE: Multiple sclerosis monitoring is based on the detection of
new lesions on brain MR imaging. Outside of study populations, MS imaging studies are …

Purpose The assessment of multiple sclerosis (MS) lesions on follow-up magnetic
resonance imaging (MRI) is tedious, time-consuming, and error-prone. Automation of low …

BACKGROUND AND PURPOSE: The detection of new subtle brain pathology on MR
imaging is a time-consuming and error-prone task for the radiologist. This article introduces …

The automatic analysis of subtle changes between MRI scans is an important tool for
assessing disease evolution over time. Manual labeling of evolutions in 3D data sets is …

BACKGROUND AND PURPOSE: The standard for evaluating interval radiologic activity in
MS, side-by-side MR imaging comparison, is restricted by its time-consuming nature and …