6 Result(s)
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Chapter and Conference Paper
Correction to: Knowledge-Guided Segmentation of Isointense Infant Brain
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Chapter and Conference Paper
Knowledge-Guided Segmentation of Isointense Infant Brain
Tissue segmentation of infants could lead to early diagnosis of neurological disorders, potentially enabling early interventions. However, the challenge of tissue quantification is increased due to the very dy...
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Chapter and Conference Paper
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Perfusion imaging is the current gold standard for acute ischemic stroke analysis. It allows quantification of the salvageable and non-salvageable tissue regions (penumbra and core areas respectively). In clin...
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Chapter and Conference Paper
Relevance Vector Machines for Harmonization of MRI Brain Volumes Using Image Descriptors
With the increased need for multi-center magnetic resonance imaging studies, problems arise related to differences in hardware and software between centers. Namely, current algorithms for brain volume quantifi...
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Chapter and Conference Paper
A Comparison of Machine Learning Approaches for Classifying Multiple Sclerosis Courses Using MRSI and Brain Segmentations
The objective of this paper is to classify Multiple Sclerosis courses using features extracted from Magnetic Resonance Spectroscopic Imaging (MRSI) combined with brain tissue segmentations of gray matter, whit...
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Chapter and Conference Paper
Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation
Quantification of white matter lesion changes on brain magnetic resonance (MR) images is of major importance for the follow-up of patients with Multiple Sclerosis (MS). Many automated segmentation methods have...
