3d chest ct 1anatomical guidance 1attention maps 1color-invariant learning 1cross-modal reasoning 1gastric endoscopy 1knowledge distillation 1medical imaging 1medical visual grounding 1neoplasm classification 1voxel-level grounding 1
From the 2 of 3 linked papers with an AI index.
3 papers
cs.CV2026
MAGE: Color-Invariant and Spatial Knowledge Distillation for Gastric Neoplasm Classification
Jiho Jun, Jeongwon Woo, Jaemin Song +6
The paper introduces MAGE, a framework that uses masked achromatic views and dual-objective knowledge distillation to train a model that classifies gastric adenoma versus carcinoma…
cs.CV2026
Decouple and Reason: Anatomically Guided Two-Stage Voxel-Level Grounding of Free-Text Findings in 3D Chest CT
Kwang-Hyun Uhm, Inhwa Son, Sung-Jea Ko
The paper introduces a two‑stage decoupled framework that first performs class‑agnostic lesion segmentation on 3D chest CT scans and then aligns the resulting sub‑volumes with free…
eess.IV2025
Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge
Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60
Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…