Computer-aided detection of mesial temporal sclerosis based on hippocampus and cerebrospinal fluid features in MR images

Publication date: Available online 28 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Huiquan Wang, S. Nizam Ahmed, Mrinal MandalAbstractMesial temporal sclerosis (MTS) is the commonest brain abnormalities in patients with intractable epilepsy. Its diagnosis is usually performed by neuroradiologists based on visual inspection of magnetic resonance imaging (MRI) scans, which is a subjective and time-consuming process with inter-observer variability. In order to expedite the identification of MTS, an automated computer-aided method based on brain MRI characteristics is proposed in this paper. It includes brain segmentation and hippocampus extraction followed by calculating features of both hippocampus and its surrounding cerebrospinal fluid. After that, support vector machines are applied to the generated features to identify patients with MTS from those without MTS. The proposed technique is developed and evaluated on a data set comprising 15 normal controls, 18 left and 18 right MTS patients. Experimental results show that subjects are correctly classified using the proposed classifiers with an accuracy of 0.94 for both left and right MTS detection. Overall, the proposed method could identify MTS in brain MR images and show a promising performance, thus showing its potential clinical utility.

Source: Biocybernetics and Biomedical Engineering - October 29, 2018 Category: Biomedical Engineering Source Type: research