Extracting 3D structures from volumetric images like MRI or CT is becoming a routine process for diagnosis based on quantitation, for radiotherapy planning, for surgical planning and image -guided intervention, for studying neurodevelopmental and neurodegenerative aspects of brain diseases, and for clinical drug trials. Key issues for segmenting anatomical objects from 3D medical images are validity and reliability. We have developed VALMET, a new tool for validation and comparison of object segmentation. New features not available in commercial and public-domain image processing packages ar e the choice between different metrics to describe differences between segmentations and the use of graphical overlay and 3D display for visual assessment of the locality and magnitude of segmentation variability. Input to the tool are an original 3D image (MRI, CT, ultrasound), and a series of segmentations either generated by several human raters and/or by automatic methods (machine). Quantitativ...