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Fig. 2 | BMC Bioinformatics

Fig. 2

From: A novel computational method for automatic segmentation, quantification and comparative analysis of immunohistochemically labeled tissue sections

Fig. 2

Immunohistochemically stained human sections showing the high color and texture variability characterizing histological images. a pyoderma gangrenosum marked with arginase antibody (Arg1); b human tonsil marked with Ki-67 antibody; c subcutaneous metastatic melanoma marked with CD163 antibody; d lymph node metastatic melanoma marked with CD163 antibody e liver cirrhosis marked with carbonic anhydrase IX antibody; f placenta marked with PDL-1 antibody; g kidney marked with V-ATPase H1 antibody; h colon marked with alcian blue. Thanks to the usage of supervised learning techniques, MIAQuant_Learn can be customized to effectively segment markers characterized by different stains and textures

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BMC Bioinformatics

ISSN: 1471-2105

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