An MRI-based deep learning approach for accurate detection of Alzheimer’s disease

Alzheimer’s disease (AD) is the most prevalent type of dementia of the nervous system that causes many brain functions to weaken (eg, memory loss). Non-invasive early diagnosis of AD has attracted a lot of research attention nowadays as early diagnosis is the most important factor in improving patient care and treatment results. This research develops a deep learning-based pipeline for accurate diagnosis and stratification of AD stages. The proposed analysis pipeline utilizes shallow Convolutional Neural Network (CNN) architecture and 2D T1-weighted Magnetic Resonance (MR) brain images. The proposed pipeline not only introduces a fast and accurate AD diagnosis module but also provides a global classification…