title: Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images.
abstract: Magnetic Resonance (MR) white matter hyperintensities have been shown to predict an increased risk of developing cognitive decline. However, their actual role in the conversion to dementia is still not fully understood. Automatic segmentation methods can help in the screening and monitoring of Mild Cognitive Impairment patients who take part in large population-based studies. Most existing segmentation approaches use multimodal MR images. However, multiple acquisitions represent a limitation in terms of both patient comfort and computational complexity of the algorithms. In this work, we propose an automatic lesion segmentation method that uses only three-dimensional fluid-attenuation inversion recovery (FLAIR) images. We use a modified context-sensitive Gaussian mixture model to determine voxel class probabilities, followed by correction of FLAIR artifacts. We evaluate the method against the manual segmentation performed by an experienced neuroradiologist and compare the results with other unimodal segmentation approaches. Finally, we apply our method to the segmentation of multiple sclerosis lesions by using a publicly available benchmark dataset. Results show a similar performance to other state-of-the-art multimodal methods, as well as to the human rater.
authors.affiliation: MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, The Netherlands. a.r.lopessimoes@utwente.nl
authors.forename: Rita
authors.initials: R
authors.lastname: Simões
authors.forename: Christoph
authors.initials: C
authors.lastname: Mönninghoff
authors.forename: Martha
authors.initials: M
authors.lastname: Dlugaj
authors.forename: Christian
authors.initials: C
authors.lastname: Weimar
authors.forename: Isabel
authors.initials: I
authors.lastname: Wanke
authors.forename: Anne-Marie
authors.initials: AM
authors.lastname: van Cappellen van Walsum
authors.forename: Cornelis
authors.initials: C
authors.lastname: Slump
mesh_terms: D000465:Algorithms; D016477:Artifacts; D054022:Cerebrum / Q000473:pathology*; D003072:Cognition Disorders / Q000175:diagnosis / Q000473:pathology; D001330:Electronic Data Processing; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009186:Myelin Sheath / Q000473:pathology*; D016011:Normal Distribution; D015588:Observer Variation; D015203:Reproducibility of Results
keywords: Automatic segmentation; Fluid-attenuation inversion recovery; Magnetic resonance imaging; White matter hyperintensities