Yunkui Pang

Training nnU-Net models for medical image segmentation with large patient samples is computationally expensive, limiting iteration speed in research and clinical translation. We present an optimized training workflow that significantly accelerates nnU-Net tra...

Accurate multi-organ auto-segmentation is essential for efficient clinical workflows. Although nnU-Net-based models like TotalSegmentator achieve strong baseline performance, residual errors can lead to boundary outliers that require time-consuming manual cor...