CrossScale-GLIO: Topology-Preserving Vision-Language Alignment of MRI and Whole-Slide Histopathology for Diffuse Glioma

arXiv:2609.28524 · eess.IV, cs.AI, q-bio.QM · Submitted 2026-08-04 · Read on arXiv

eess.IV, cs.AI, q-bio.QM

Submitted: 2026-08-04

Updated: 2026-08-04

Terminology

• AUROC — 16× in this paper · explained in 2 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Transformer — 7× in this paper · explained in 2 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Optimal Transport — 6× in this paper · explained in 5 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Late Fusion — 4× in this paper · explained in 2 episodes
• AUC — 3× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Graph Construction — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• External Validation — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Actionability — 1× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Data Fusion — 1× in this paper · explained in 3 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification

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