Caligiuri Maria Eugenia, Perrotta Paolo, Augimeri Antonio, Rocca Federico, Quattrone Aldo, Cherubini Andrea
Neuroimaging Unit, Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Germaneto, CZ, Italy.
Neuroinformatics. 2015 Jul;13(3):261-76. doi: 10.1007/s12021-015-9260-y.
White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular disorders. A truly reliable and fully automated method for quantitative assessment of WMH on magnetic resonance imaging (MRI) has not yet been identified. In this paper, we review and compare the large number of automated approaches proposed for segmentation of WMH in the elderly and in patients with vascular risk factors. We conclude that, in order to avoid artifacts and exclude the several sources of bias that may influence the analysis, an optimal method should comprise a careful preprocessing of the images, be based on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives. All these features should not exclude computational leanness and adaptability to available data.
脑白质高信号(WMH)常见于健康老年人以及患有多种神经和血管疾病的患者的大脑中。目前尚未找到一种真正可靠且完全自动化的方法来在磁共振成像(MRI)上对WMH进行定量评估。在本文中,我们回顾并比较了大量针对老年人及有血管危险因素患者的WMH分割所提出的自动化方法。我们得出结论,为了避免伪影并排除可能影响分析的多种偏差来源,一种最佳方法应包括对图像进行仔细的预处理,基于多模态、互补数据,考虑病变的空间信息并校正假阳性。所有这些特征不应排除计算的简洁性以及对可用数据的适应性。