A three-stage framework combines dual-head CNNs, saliency attribution, neuroanatomical atlas mapping, and LLMs to generate interpretable reports for brain tumor classification on MRI images.
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Bridging visual saliency and large language models for explainable deep learning in medical imaging
A three-stage framework combines dual-head CNNs, saliency attribution, neuroanatomical atlas mapping, and LLMs to generate interpretable reports for brain tumor classification on MRI images.