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Introduction:The complexity of histopathological images remains a challengingissueincancerdiagnosis.Apathologistanalysesimmunohistochemicalimages to detect a colour-based stain, which is brown for positive nuclei with different intensitiesandbluefornegativenuclei.Severalissuesemergeduringtheeyeballing tissue slide analysis, such as colour variations caused by stain inhomogeneity, non-uniform illumination, irregular cell shapes, and overlapping cell nuclei. To overcome those problems, an automated computer-aided diagnosis system is proposedtosegmentandquantifydigestiveneuroendocrinetumours. Material and methods:We present a novel pre-processing approach based on colourspaceassessment.Acriterioncalledpertinencedegreeisintroducedtoselect theappropriatecolourchannel,followedbycontrastenhancement.