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Biomedical Engineering and Bioengineering

Western University

Series

Diffusion Tensor Imaging

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Engineering

In Vivo Mri Signatures Of Hippocampal Subfield Pathology In Intractable Epilepsy., Maged Goubran, Boris C Bernhardt, Diego Cantor-Rivera, Jonathan C Lau, Charlotte Blinston, Robert R Hammond, Sandrine De Ribaupierre, Jorge G Burneo, Seyed M Mirsattari, David A Steven, Andrew G Parrent, Andrea Bernasconi, Neda Bernasconi, Terry M Peters, Ali R Khan Jan 2015

In Vivo Mri Signatures Of Hippocampal Subfield Pathology In Intractable Epilepsy., Maged Goubran, Boris C Bernhardt, Diego Cantor-Rivera, Jonathan C Lau, Charlotte Blinston, Robert R Hammond, Sandrine De Ribaupierre, Jorge G Burneo, Seyed M Mirsattari, David A Steven, Andrew G Parrent, Andrea Bernasconi, Neda Bernasconi, Terry M Peters, Ali R Khan

Robarts Imaging Publications

OBJECTIVES: Our aim is to assess the subfield-specific histopathological correlates of hippocampal volume and intensity changes (T1, T2) as well as diff!usion MRI markers in TLE, and investigate the efficacy of quantitative MRI measures in predicting histopathology in vivo.

EXPERIMENTAL DESIGN: We correlated in vivo volumetry, T2 signal, quantitative T1 mapping, as well as diffusion MRI parameters with histological features of hippocampal sclerosis in a subfield-specific manner. We made use of on an advanced co-registration pipeline that provided a seamless integration of preoperative 3 T MRI with postoperative histopathological data, on which metrics of cell loss and gliosis were quantitatively …


Detection Of Temporal Lobe Epilepsy Using Support Vector Machines In Multi-Parametric Quantitative Mr Imaging., Diego Cantor-Rivera, Ali R Khan, Maged Goubran, Seyed M Mirsattari, Terry M Peters Jan 2014

Detection Of Temporal Lobe Epilepsy Using Support Vector Machines In Multi-Parametric Quantitative Mr Imaging., Diego Cantor-Rivera, Ali R Khan, Maged Goubran, Seyed M Mirsattari, Terry M Peters

Robarts Imaging Publications

The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this domain, we propose a method that combines quantitative relaxometry and diffusion tensor imaging (DTI) with support vector machines (SVM) aiming to improve TLE detection. The main contribution of this work is two-fold: on one hand, the feature selection process, principal component analysis (PCA) transformations of the feature space, and SVM parameterization are analyzed as factors constituting a classification …