AI-powered deeplearningmodel can improve cancer diagnostics by accurately counting cell types in whole slide images
Predicting the presence and counting various cell types in the tumor micro-environment is crucial for identifying cell spatial and morphological features in computational pathology. Deep learning approaches have been used extensively in predicting and counting different cell types in whole slide images . However, DL-based probabilistic approaches have limitations in classifying pixels and determining cellular boundaries.
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