Shape-to-graph mapping method for efficient characterization and classification of complex geometries in biological images
Fig 16
Sensitivity to over- and under-thresholding.
The features of the graph capture the variations in the pattern resulted due to a suboptimal segmentation process, which emphasizes the importance of preserving the proper image content at the pre-processing steps. A. A gray-scale image of endothelial cells forming an interconnected mesh. B. Boundary and width profiles for the subgraph associated with the boundary of the large hole in the middle of the image. C. All in-graphs of the pattern (top row) and a single subgraph associated with the hole boundary (bottom row) for the threshold values that are too low (left), optimal (middle), and too high (right). Under-thresholding can expand the pattern and create artificial (non-existing) connections between cells or cell clusters, while over-thresholding can shrink the pattern and create artificial (non-existing) holes or break the existing contacts.