Automatic white matter lesion segmentation using contrast enhanced FLAIR intensity and Markov Random Field

Highlights • An automatic method for white matter lesion segmentation (WML). • A novel filter is used to enhance the contrast of WML. • A robust Markov Random Field is used to remove false positive WMLs. • Evaluated with respect to the grading of two expert graders. • Compared with state of the art...

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Veröffentlicht in:	Computerized medical imaging and graphics 2015-10, Vol.45, p.102-111
Hauptverfasser:	Roy, Pallab Kanti, Bhuiyan, Alauddin, Janke, Andrew, Desmond, Patricia M, Wong, Tien Yin, Abhayaratna, Walter P, Storey, Elsdon, Ramamohanarao, Kotagiri
Format:	Artikel
Sprache:	eng
Schlagworte:	Brain - pathology Cerebrovascular diseases Computer Simulation Contrast Media Data Interpretation, Statistical Diffusion Tensor Imaging - methods Humans Image Interpretation, Computer-Assisted - methods Internal Medicine Leukoencephalopathies - pathology Machine Learning Magnetic resonance imaging (MRI) Markov Chains Markov Random Field (MRF) Models, Statistical Observer Variation Other Pattern Recognition, Automated - methods Random forest (RF) Reproducibility of Results Sensitivity and Specificity Subtraction Technique White Matter - pathology White matter lesions (WMLs)
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