CMViM: Contrastive Masked Vim Autoencoder for 3D Multi-modal Representation Learning for AD classification

arXiv:2403.16520v1 Announce Type: new
Abstract: Alzheimer's disease (AD) is an incurable neurodegenerative condition leading to cognitive and functional deterioration. Given the lack of a cure, prompt and precise AD diagnosis is vital, a complex process dependent on multiple factors and multi-modal data. While successful efforts have been made to integrate multi-modal representation learning into medical datasets, scant attention has been given to 3D medical images. In this paper, we propose Contrastive Masked Vim Autoencoder (CMViM), the first efficient representation learning …

abstract alzheimer's arxiv autoencoder classification cognitive cs.cv cure data diagnosis disease functional modal multi-modal multiple process prompt representation representation learning type vim vital