Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification
In histopathology, human experts primarily rely on color as a means of enhancing contrast to interpret tissue morphology, whereas machine vision models process color as raw statistical information. This distinction raises a fundamental question: to what extent can pixel intensity alone, independent of structural and morphological cues, support cancer classification? To address this question, we systematically evaluated the standalone discriminative power of global color features while deliberately excluding all morphological information. Specifically, we extracted statistical color moments and discretized RGB and HSV color histograms, and assessed their performance across ten diverse expe...
| Authors | Farnaz Kheiri, Shahryar Rahnamayan, Masoud Makrehchi |
|---|---|
| Primary category | cs.CV |
| Published | 18 May 2026 |
| Last updated at source | 18 May 2026 |
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