Proposes TopoAgent, an LLM agent framework that automatically selects and configures topological descriptors from persistent homology for medical image analysis without task-specific training.
gradient histograms: A comparative study for medical image classification
2 Pith papers cite this work. Polarity classification is still indexing.
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A TDA-ViT fusion model reports 99.10% accuracy on four-class brain tumor classification using the BRISC2025 dataset.
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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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Bridging Topology and Deep Representation Learning: A TDA-ViT Fusion Model for Four-Class Brain Tumor Classification
A TDA-ViT fusion model reports 99.10% accuracy on four-class brain tumor classification using the BRISC2025 dataset.