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.
© COPYRIGHT Society of Photo-Optical Instrumentation Engineers . Downloading of the abstract is permitted for personal use only.
Source: Education Headlines (educationheadlines.net)
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