Accurate quantification of white matter hyperintensities (WMH) from MRI is a valuable tool for studies on ageing and neurodegeneration. Reliable automatic extraction of WMH biomarkers is challenging, primarily due to their heterogeneous spatial occurrence, their small size and their diffuse nature. In this paper, we present an automatic and accurate method to segment these le-sions that is based on the use of neural networks and an overcomplete strategy. The proposed method was compared to other related methods showing competitive and reliable results in two different neurodegenerative datasets.
['José V. Manjón', 'Pierrick Coupé', 'Parnesh Raniga', 'Ying Xia', 'Jurgen Fripp', 'Olivier Salvado']
HIST: HyperIntensity Segmentation Tool