Figure 2.

Principle of image annotation, block-based feature extraction and classification. Areas representative of pure tumor epithelium and stroma were identified in the digitized tissue microarray spots (A) and then split into blocks of size 80 × 80 pixels (B). A local binary pattern (LBP/C) operator was applied to the blocks and block-specific LBP histograms generated (C). The block histograms are then used as input to a support vector machine (SVM) classifier (D), which assigns a tissue category (epithelium or stroma) score to the block. The SVM score for each block is pseudo colored to visualize the output (E), and the average block score is taken to represent the predicted class of an image (F)

Linder et al. Diagnostic Pathology 2012 7:22   doi:10.1186/1746-1596-7-22
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