Zongwei Zhou

Routine clinical reports and historical scans can entirely replace manual voxel annotations, yielding dense tumor segmenters that outperform supervised public baselines at zero labeling cost.

In-context memory plateaus fast during interactive 3D segmentation, but turning clinician clicks into meta-learned test-time gradient steps halves human correction effort while cutting volumetric failure rates by over 40%.

AI-generated liver MRI reports can achieve 76% case-level sensitivity and are rated clinically acceptable by radiologists, challenging the status quo of manual reporting.

Current AI models miss critical tumor detections in underrepresented demographics, revealing a hidden bias that could compromise patient outcomes.

Unlock the power of cutting-edge photon-counting CT imaging on your existing routine chest CT scans, boosting lesion detection by 10-15%.