Hierarchical Differential MedViT-3D: Specialized Hybrid Transformer for Multiclass Diagnosis of Neurodegenerative Diseases
Abstract
Differential diagnosis of neurodegenerative diseases using 3D T1w MRI remains a challenge, particularly when distinguishing between clinically similar dementia subtypes. While deep learning has achieved high performance on binary screening (e.g., controls vs. Alzheimer’s Disease), standard architectures often struggle with the class imbalance and subtle anatomical variations, leading to a critical trade-off between global specificity and focal sensitivity. In this work, we propose a hybrid Dual-Stream framework using a Hierarchical Differential MedViT-3D. First, a fine-scale stream adapts the MedViTV2 architecture to 3D and adds recent Differential Attention and Rotary Positional Embeddings (RoPE) mechanisms to capture focal anomalies that standard attention misses. Second, to counter the “vanishing specificity” of such high-sensitivity models, we fuse this focal stream with global volumetric priors and …