Detail Inovasi Perguruan Tinggi

Tema: Pengolahan Sinyal Informasi (PSI)
Judul: Hippocampal Segmentation using Structured Extreme Learning Machine with Bag of Features
Perguruan Tinggi: Universitas Telkom
Jenis/sdm: dosen/0425068601

Tahun: 2017

Automatic hippocampal segmentation is one of the technique used by experts to extract hippocampal to help them diagnose for any brain related disease. In this paper, we are going to introduce an automatic segmentation technique where Structured Extreme Learning Machine (S-ELM) will be used to segment hippocampal. The objective of this paper is mainly to investigate on the performance of the Structured Extreme Learning Machine (S-ELM) where every hyperparameter used will be analyzed. This technique will be employed on the ADNI dataset where Bag of Feature (BoF) will be used as the feature extraction to locate hippocampus from the observed MRI. Constructing BoF can be based on feature point location through salient point, regular grid, random point and the combination of all aforementioned feature point locations. The results show that S-ELM can locate the hippocampal region by using grid point selection method compare with another feature point that we have proposed.