When pathology segmentation learns to listen
Nature
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Researchers have developed a pathology segmentation model guided by natural language, enabling the system to connect pathological terms with image content to create semantic masks. This approach aims to make computational pathology more flexible, interpretable, and aligned with human expertise.
