Elizabeth M. Sweeney

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BACKGROUND AND PURPOSE Detecting incidence and enlargement of lesions is essential in monitoring the progression of MS. In clinical trials, lesion load is observed by manually segmenting and comparing serial MR images, which is time consuming, costly, and prone to inter- and intraobserver variability. Subtracting images from consecutive time points nulls(More)
Cerebral microbleeds (CMB) are a common marker of traumatic brain injury. Accurate detection and quantification of the CMBs are important for better understanding the progression and prognosis of the injury. Previous microbleed detection methods have suffered from a high rate of false positives, which is time consuming to manually correct. In this paper, we(More)
AIM To compare indices of respiratory failure in terms of their ability to predict adverse respiratory outcomes in preterm infants. The indices evaluated were: (a) the alveolar-arterial oxygen tension difference (A-aDO(2)); (b) the ratio of arterial to alveolar oxygen tension (a/A ratio); (c) the oxygenation index (OI); (d) the fractional inspired oxygen(More)
We present the package fslr, a set of R functions that interface with FSL (FMRIB Software Library), a commonly-used open-source software package for processing and analyzing neuroimaging data. The fslr package performs operations on 'nifti' image objects in R using command-line functions from FSL, and returns R objects back to the user. fslr allows users to(More)
Quantitative T1 maps estimate T1 relaxation times and can be used to assess diffuse tissue abnormalities within normal-appearing tissue. T1 maps are popular for studying the progression and treatment of multiple sclerosis (MS). However, their inclusion in standard imaging protocols remains limited due to the additional scanning time and expert calibration(More)
Brain lesion localization in multiple sclerosis (MS) is thought to be associated with the type and severity of adverse health effects. However, several factors hinder statistical analyses of such associations using large MRI datasets: 1) spatial registration algorithms developed for healthy individuals may be less effective on diseased brains and lead to(More)
Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect, and other(More)
The formation of multiple sclerosis (MS) lesions is a complex process involving inflammation, tissue damage, and tissue repair - all of which are visible on structural magnetic resonance imaging (MRI) and potentially modifiable by pharmacological therapy. In this paper, we introduce two statistical models for relating voxel-level, longitudinal,(More)
Multiple sclerosis (MS) is an immune-mediated neurological disease that causes morbidity and disability. In patients with MS, the accumulation of lesions in the white matter of the brain is associated with disease progression and worse clinical outcomes. Breakdown of the blood-brain barrier in newer lesions is indicative of more active disease-related(More)
We provide software tools for displaying and publishing interactive 3-dimensional (3D) and 4-dimensional (4D) figures to html webpages, with examples of high-resolution brain imaging. Our framework is based in the R statistical software using the rgl package, a 3D graphics library. We build on this package to allow manipulation of figures including rotation(More)