A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes
S. M. Nuruzzaman Nobel,
S. M. Masfequier Rahman Swapno,
Md Babul Islam
et al.
Abstract:Glioblastoma is the most common adult brain tumor, significantly impacts disability and mortality. Early and accurate diagnosis of glioma subtypes is essential, but manual categorization is challenging due to their complexity, prompting the need for automated solutions. We developed an innovative mixed convolution‐transformer model to classify glioma subtypes, including astrocytoma, glioblastoma, oligodendroglioma, and normal brain tissue, using whole slide images. The novelty of this model lies in its remarka… Show more
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