Automatic segmentation in MR brain images is important for quantitative analysis in large-scale
studies with images acquired at all ages. This paper presents a method for the automatic …

Many methods have been proposed for tissue segmentation in brain MRI scans. The
multitude of methods proposed complicates the choice of one method above others. We have …

Noise filtering techniques that maintain image contrast while decreasing image noise have
the potential to optimize the quality of computed tomography (CT) images acquired at …

Automatic segmentation of brain tissues and white matter hyperintensities of presumed
vascular origin (WMH) in MRI of older patients is widely described in the literature. Although …

Introduction Pooling of multicenter brain imaging data is a trend in studies on ageing related
brain diseases. This poses challenges to MR-based brain segmentation. The performance …

Cerebral computed tomography perfusion (CTP) scans are acquired to detect areas of
abnormal perfusion in patients with cerebrovascular diseases. These 4D CTP scans consist of …

Purpose To suggest a simple and robust technique used to reconstruct high-quality computed
tomographic (CT) angiographic images from CT perfusion data and to compare it with …

Background The segmentation of brain tissue into cerebrospinal fluid, gray matter, and white
matter in magnetic resonance imaging scans is an important procedure to extract regions of …

In a broad range of fields it may be desirable to reuse a supervised classification algorithm
and apply it to a new data set. However, generalization of such an algorithm and thus …

We introduce a novel surrogate-assisted Genetic Algorithm (GA) for expensive optimization
of problems with discrete categorical variables. Specifically, we leverage the strengths of the …