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MorphoNet: Morphological Sub-region-based Structure Learning for WSI Analysis
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DOI：10.1016/j.media.2026.104061.png)
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Abstract
En 中文
• Propose MorphoNet framework to capture morphological patterns and long-range tissue structures in WSIs. • Develop a Morphological Sub-Region Grouping mechanism to model WSIs as spatially coherent sub-regions. • Introduce a spatial-aware clustering approach and a sub-region aggregation strategy to derive sub-region embeddings. • Achieve superior performance across 10 public benchmarks, outperforming state-of-the-art methods in tumor subtyping and survival prediction.
Keywords:
WSI Representation Learning
Graph Learning
Computational Pathology
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