Diagnosis of Alzheimer’s Disease Using Convolutional Neural Network With Select Slices by Landmark on Hippocampus in MRI Images

Alzheimer’s disease (AD) is a major public health priority. Hippocampus one of the most affected areas brain and easily accessible as biomarker using MRI images in machine learning for diagnosing AD. In learning, entire image slices showed lower accuracy AD classification. We present select method by landmarks on hippocampus region images. This study aims to see which views have higher Then, get value three categories, we used multiclass classification with publicly available Disease Neuroimaging Initiative (ADNI) dataset Resnet50 LeNet. The models were total 4,500 categories. Our demonstrated that selecting performed better than improves coronal view accuracy. played significant role improving performance. results similar medical experts usually diagnose also found LeNet became potential model