Until the introduction of non-invasiveimaging techniques, the representation of anatomy and pathology relied solely on gross dissection and histological staining. Computerized Tomography (CT) and Magnetic Resonance Imaging (MRI) protocols allow for the clinical evaluation of anatomical images derived from complementary modalities, thereby increasing reliability of the diagnosis and the prognosis of disease. Despite the significant improvements in image contrast and resolution of MRI, autopsy and classical histopathological analysis are still indispensable for the correct diagnosis of specific disease. It is therefore important to be able to correlate multiple images from different modalities, in vivo and postmortem, in order to validate non-invasive imaging markers of disease. To that effect, we have developeda methodologicalpipeline and a visualization environment that allow for the concurrentobservation of both macroscopic and microscopic image data relative to the same patient. We describe these applications and sample data relative to the study of the anatomy and disease of the Central Nervous System (CNS). The brain is approached as an organ with a complex 3-dimensional (3-D) architecture that can only be effectively studied combining observation and analysis at the system level as well as at the cellular level. Our computational and visualization environment allows seamless navigation through multiple layers of neurological data that are accessible quickly and simultaneously.