Proposes TopoAgent, an LLM agent framework that automatically selects and configures topological descriptors from persistent homology for medical image analysis without task-specific training.
arXiv preprint arXiv:2507.01171 (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
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MS-COOT uses co-optimal transport on hypergraph representations of Morse-Smale complexes to enable explicit region-to-region matching for identifying structural events such as splitting and merging.
citing papers explorer
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TopoAgent: An Agentic Framework for Automated Topology Learning in Medical Imaging
Proposes TopoAgent, an LLM agent framework that automatically selects and configures topological descriptors from persistent homology for medical image analysis without task-specific training.
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MS-COOT: Comparing Morse-Smale Complexes with Co-Optimal Transport
MS-COOT uses co-optimal transport on hypergraph representations of Morse-Smale complexes to enable explicit region-to-region matching for identifying structural events such as splitting and merging.