Leveraging Deep Learning and Xception Architecture for High-Accuracy MRI Classification in Alzheimer Diagnosis

arXiv:2403.16212v1 Announce Type: cross
Abstract: Exploring the application of deep learning technologies in the field of medical diagnostics, Magnetic Resonance Imaging (MRI) provides a unique perspective for observing and diagnosing complex neurodegenerative diseases such as Alzheimer Disease (AD). With advancements in deep learning, particularly in Convolutional Neural Networks (CNNs) and the Xception network architecture, we are now able to analyze and classify vast amounts of MRI data with unprecedented accuracy. The progress of this technology not only enhances our understanding …

abstract accuracy application architecture arxiv classification cs.cv cs.lg deep learning diagnosis diagnostics disease diseases eess.iv imaging medical mri perspective technologies type