The Feature Extraction Software is a flexible tool to extract and visualize a variety of image features from large images (Giga Bytes size). It supports over 30 distinct features that can be parametrized, which can be extracted from different user-defined regions of interest. It is implemented in the Java programming language and can run locally on a desktop or take advantage of parallel computing on a cluster (e.g. Hadoop). Figure 1 illustrates hexagon spatial regions partitioning stem cell colonies that are color-coded based on the extracted average intensity value.
Figure 2 illustrates the options for extracting image features with or without a mask, and with other options with a mask that enable feature extractions over various regions of interest.
The extracted features are outputted by default as CSV tables. When extracting features on a number of different images (e.g. evolution of colonies over time), the CSV tables can be merged into a single sqlite database, facilitating data-mining on the dataset.