RT-Super: Learning Tumor Segmentation from Longitudinal Images and Reports

arXiv:2609.35637 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/MrGiovanni/RT-Super

Terminology

• Transformer — 23× in this paper · explained in 2 episodes
• Consistency — 15× in this paper · explained in 3 episodes
• Distillation — 9× in this paper · explained in 2 episodes
• nnU-Net — 6× in this paper · explained in 2 episodes
• AUC — 5× in this paper · explained in 2 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Segmentation Masks — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Foundation Model — 3× in this paper · explained in 3 episodes
• Self-Distillation — 3× in this paper · explained in 7 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Universal Lesion Segmentation — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Longitudinal Data — 1× in this paper · explained in 2 episodes
• Mixture of Experts — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Teacher-Student Distillation — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks
• Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset
• Are Vision Language Models Ready for Clinical Diagnosis? A 3D Medical Benchmark for Tumor-centric Visual Question Answering
• A Data-scalable Transformer for Medical Image Segmentation: Architecture, Model Efficiency, and Benchmark
• The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes
• Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomography
• RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiology
• MedGemma Technical Report

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