Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach - Wagner, Marcus; Hänsel, René; Reinke, Sarah; Richter, Julia; Altenbuchinger, Michael; Braumann, Ulf-Dietrich; Spang, Rainer; Löffler, Markus; Klapper, Wolfram (Biological Procedures Online)
We describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies.