Yingtai Li
ytai
- China
- University of Science & Technology of China
- School of Biomedical Engingeering
Statistics
- Member for 2 weeks, 5 days
- 2 challenge submissions
Activity Overview
Task 1: Radiology Report Generation
Challenge UserParticipants build vision‑language models that translate a complete 3‑D chest CT scan into a free‑text radiology report covering findings and impression; performance is assessed with standard NLG scores (BLEU, METEOR, ROUGE‑L) plus the clinically aware CRG metric, using the CT‑RATE dataset split into public train/validation and hidden internal+external test sets.
Task 2: Multi-Abnormality Classification
Challenge UserGiven a volumetric chest CT, algorithms must output an 18‑length binary vector indicating the presence of common thoracic conditions (e.g., pleural effusion, lung nodule); evaluation on hidden test cohorts combines AUROC, F1, Precision, Recall, and Accuracy, with point‑based ranking driven by permutation‑test wins.
Task 4: Text-Conditional CT Generation
Challenge UserWithout voxel‑level labels during training, systems must localize five key pathologies—pericardial effusion, pleural effusion, consolidation, lung opacity, and lung nodule—producing 3‑D heat‑maps that are scored on Dice, IoU, Hausdorff‑95, and Sensitivity against expert masks for 2000 hidden test scans.
