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A deep convolutional neural network for classification of red blood cells in sickle cell anemia

Fig 4

Workflow of RBC patch generation from ROIs with touching RBCs.

(A) ROI patch. (B) binary ROI mask image. (C) Euclidean distance transfrom result. (D) Probability map based on random walk method with seeds (green dots) obtained from distance transform result. (E) separated RBC binary mask. (F) segmented RBC outlines (red line). (G) bounding boxes of single RBCs. (H) The touching RBCs are separated into four single RBC patches.

Fig 4

doi: https://doi.org/10.1371/journal.pcbi.1005746.g004