White matter hyperintensities (WMH) are present in various dementia types, but are particularly associated with vascular dementia (VaD). The NINDS-AIREN criteria, used for clinical diagnosis of VaD, suggest a WMH load of over 25% of total white matter as a diagnostic criterion. Automated WMH assessment methods have been applied to a range of patient groups, and the load and location of WMH provide useful information for both dementia diagnosis, and differentiation between dementia types. To bring quantitative tools into clinical practice, the data must be placed in context, and we present an automated tool that provides a summary report based on quantitative assessment of global and regional WMH. Automated quantification of WMH is performed using T1W MRI and FLAIR images, based on an in-house implementation of the “LST: Lesion Segmentation Tool” (http://www.applied-statistics.de/lst.html). The percentage of WMH within total white matter is computed, as well as the percentage of WMH within four regions of interest (juxtacortical, periventricular, deep, and juxtacortical). We performed preliminary validation of the method in 43 subjects with clinically diagnosed dementia. In the patient report, we indicate that the patient meets clinical imaging criteria for VaD if over 25% of total white matter constitutes WMH. Based on analysis of test data for which visually rated Fazekas scores were available, we determined that 5-25% WMH indicates a likely micro-vascular component of symptoms, and below 5% WMH that symptoms are unlikely to be caused by micro-vascular disease. Validation tests revealed dice overlap between manual and automated segmentations of 0.46. This is comparable with other state-of-the-art automated methods. Good correlation coefficients between manual and automated WMH volumes were also found, R = 0.81 for total WMH, R = 0.86 for juxtaventricular WMH, R = 0.84 for periventricular WMH, R = 0.78 for deep WMH, and R = 0.81 for juxtacortical WMH.