Applicability of semi-automatic segmentation for volumetric analysis of brain lesions

Abstract

This project involves the development of a fast semi-automatic segmentation procedure to make an accurate volumetric estimation of brain lesions. This method has been applied in the segmentation of demyelination plaques in Multiple Sclerosis (MS) and right cerebral hemispheric infarctions in patients with neglect. The developed segmentation method includes several image processing techniques, such as image enhancement, amplitude segmentation, and region growing. The entire program operates on a PC-based computer and applies graphical user interfaces. Twenty three patients with MS and 43 patients with right cerebral hemisphere infarctions were studied on a 0.5 T MRI unit. The MS plaques and cerebral infarctions were thereafter segmented. The volumetric accuracy of the program was demonstrated by segmenting Magnetic Resonance (MR) images of fluid filled syringes. The relative error of the total volume measurement based on the MR images of syringes was 1.5%. Also the repeatability test was carried out as inter- and intra-observer study in which MS plaques of six randomly selected patients were segmented. These tests indicated 7% variability in the inter-observer study and 4% variability in the intra-observer study. Average time used to segment and calculate the total plaque volumes for one patient was 10 min. This simple segmentation method can be utilized in the quantitation of anatomical structures, such as air cells in the sinonasal and temporal bone area, as well as in different pathological conditions, such as brain tumours, intracerebral haematomas and bony destructions.