Image heterogeneity does not have a mathematical definition but it is used in describing image regions. We developed a model to automatically and accurately characterize stem cell colonies into three categories. The colony categories are described by cell biologists as heterogeneous, homogeneous or dark, and shown in Figure 1. Three interactive visualisation tools help understand the complex nature of stem cells behavior and evolution.
The stem cell colonies exhibit various texture appearance, such as Homogeneous, Heterogeneous, Dark or a mix of those.
A predictive model has been designed, to automatically assess and characterize the texture of each colony based on expert's inputs. The model works at a multi-resolution level. First, it analyzes local properties of the colonies, and then aggregates them at the colony level. Despite a small number of labels provided by experts, the prediction accuracy is over 97% over a five-fold cross-validation evaluation.
The prediction results are accessible in three browser friendly interactive visualizations accesible via URL. Screen captures of the visualizations are shown below.
Figure 2: The colony predictions' map (interact by hovering mouse and dragging items)
Figure 3: The augmented lineage tree interacts by zooming, panning and hovering
Figure 4: The feature selection optimization process interacts by hovering mouse