Dentate nuclei (DN) segmentation is necessary for assessing whether DN are affected by pathologies through quantitative analysis of parameter maps, e.g. calculated from diffusion weighted imaging (DWI). This study developed a fully automated segmentation method using non-DWI (b0) images. A Convolution Neural Network was optimised on heathy subjects’ data with high spatial resolution and was used to segment the DN of Temporal Lobe Epilepsy (TLE) patients, using standard DWI. Statistical comparison of microstructural metrics from DWI analysis, as well as volumes of each DN, revealed altered and lateralised changes in TLE patients compared to healthy controls.