University of Indonesia, Indonesia
Title: Texture and gene expression analysis of the brain in detection of Alzheimer’s disease
Alhadi Bustamam is a senior lecturer and researcher in the chair of Department of Mathematics, FMIPA Universitas Indonesia (UI), at Depok INDONESIA. He is also in charge as the chair of Indonesian Mathematical Society (IndoMS) for West Java, DKI Jakarta and Banten sections. His academic background are B.Sc in Computational Mathematics UI (1996), M.Sc in Parallel Computing UI (2002) and Ph.D in Bioinformatics from Institute for Molecular Bioscience, The University of Queensland (UQ), Australia. His research interests are in the field of Bioinformatics, Advanced Computing and Biomedical Information. He is a co-founder of Advanced Computing and Bioinformatics Research Group UI.
Alzheimer’s disease as one type of dementia can cause problems to human memory, thinking and behavior. This disease causes cell death and tissue nerves damage in the brain. The brain damage can be detected using brain volume, whole brain form and genetic testing. In this research, we proposed texture analysis of the brain and genomic analysis to detect Alzheimer’s disease. The 2D and 3D MRI images were chosen to analyze texture of the brain and microarray data were chosen to analyze gene expression. We classified Alzheimer’s disease into three classes, Alzheimer’s, Mild Cognitive Impairment (MCI) and normal. In this study, texture analysis was done by using Advance Local Binary Pattern (ALBP) and Gray Level Co-occurrence Matrix (GLCM). Another method, we proposed was biclustering method to analyze microarray data. The experimental results from texture analysis showed that ALBP was better than GLCM in classification of Alzheimer’s disease. ALBP method achieved the average value of accuracy between 80%-100% for both the whole brain and hippocampus data. Furthermore, microarray data can show good performance to bicluster of gene expression data influence Alzheimer’s disease with total of bicluster is 6.