A novel deep learning-based approach for liver segmentation from 3D CT images using probabilistic shape guidance
Researchers have developed a new deep learning framework called DPUX-Net to improve liver segmentation in 3D CT scans. By combining probabilistic shape maps with a dual-path architecture, the system achieves high accuracy in identifying liver boundaries despite anatomical variations.
Why it matters
Enhanced medical imaging segmentation is critical for improving the precision of computer-aided diagnosis systems in oncology and surgery.
Scientific Reports ( 2026 ) Cite this article
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