The paper describes the application of new semi-automatic segmentation software to the task of detection of anatomical structures and lesion and their three-dimensional (3D) visualisation in 23 patients with secondary progressive multiple sclerosis (MS). The purpose is to study the correlation between magnetic resonance imaging (MRI) parameters (volumes of plaques and cerebrospinal fluid spaces) and clinical deficits (neurological deficits in the form of EDSS and RFSS scores, and neuropsychological deficits). The software operates in PC/Windows and PC/NeXTstep environments and utilises graphical user interfaces. Quantitative accuracy is measured by performing segmentation of fluid-filled syringes (relative error of 1.5%), and reproducibility is measured by intra- and inter-observer studies (3% and 7% variability, respectively). The mean volumes of MS plaques show significant correlations with the total RFSS scores (p = 0.04). Relative intracranial cerebrospinal fluid (CSF) space volumes show statistically significant correlation with EDSS scores (p = 0.01). The mean volume of MS plaques shows a significant correlation with the overall neuropsychological deficits (p = 0.03). 3D visualisation helps to understand the relationship of lesions to the surrounding brain structures. The use of semiautomatic segmentation techniques is recommended in the clinical diagnosis of MS patients.