Global color moments and RGB/HSV histograms alone support binary benign-malignant classification at up to 89% accuracy with classical ML classifiers, substantially above random baselines.
Structure-preserving color normalization and sparse stain separation for histological images.IEEE transactions on medical imaging, 35(8):1962–1971
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Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification
Global color moments and RGB/HSV histograms alone support binary benign-malignant classification at up to 89% accuracy with classical ML classifiers, substantially above random baselines.