In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion
segmentation challenge providing training and test data to registered participants. The …

Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …

Intensity normalization is an important pre-processing step in the study and analysis of
Magnetic Resonance Images (MRI) of human brains. As most parametric supervised …

With the ever-increasing amount of anatomical information radiologists have to evaluate for
routine diagnoses, computational support that facilitates more efficient education and clinical …

Longitudinal analysis of white matter lesion changes on serial MRI has become an important
parameter to study diseases with white-matter lesions. Here, we build on earlier work on …

Multiple Sclerosis (MS) lesions' segmentation is difficult due to their variegated sizes,
shapes, and intensity levels. Besides this, the class imbalance problem and the availability …

Detection of new Multiple Sclerosis (MS) lesions on magnetic resonance imaging (MRI) is
important as a marker of disease activity and as a potential surrogate for relapses. We …

Purpose To propose and evaluate a new automated method for the identification of
new/enlarging multiple sclerosis (MS) lesions on subtracted images (SI). The subtraction of …

We introduce a mass-univariate framework for the analysis of whole-brain structural
trajectories using longitudinal Voxel-Based Morphometry data and Bayesian inference. Our …

Malfunctions in the immune system cause multiple sclerosis (MS), which initiates mild to
severe nerve damage. MS will disturb the signal communication between the brain and …