Benchmarking Deep Segmentation Architectures for Histopathological Nuclei Segmentation: A Controlled Study of Transfer Learning, Robustness, and Efficiency Across CNN, Transformer, and Hybrid Models
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Accurate nuclei segmentation is essential for quantitative histopathological analysis and downstream clinical applications such as cancer grading, biomarker assessment, and prognostic modeling. Although deep learning has substantially advanced biomedical image... ...
