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Important brain parts like hippocampal usually being manually segmented by doctors. But with the introduction of hybrid between machine learning along with neuroimaging technique, it has proved to shows some promising results regarding on segmenting subcortical structures. However, it is known that Extreme Learning Machine (ELM) is to be superior machine learning technique. This study will investigate on the usage of ELM to segment hippocampal by using various hidden nodes configuration. This study also will address on the usage of full image and region of interest (ROI) using ELM. Bag of features is used as a feature extractor where it will segment the hippocampal of the MRI in order to get its visual words. ELM will used it to learn its feature. Results shows that with suitable hidden nodes, it could achieve up to 100% performance on both cases for full image and ROI in hippocampal segmentation.