Experimenters in biomedical image processing rely on software libraries to provide a large number of standard filtering and image handling algorithms. The Insight Toolkit (ITK) is an open-source library that provides a complete framework for a range of image processing tasks, and is specifically aimed at segmentation and registration tasks for both two and three dimensional images. This paper describes a visual dataflow language, ITKBoard, designed to simplify building, and more significantly, experimenting with ITK applications. The ease with which image processing experiments can be interactively modified and controlled is an important aspect of the design. The experimenter can focus on the image processing task at hand, rather than worry about the underlying software. ITKBoard incorporates composite and parameterised components, and control constructs, and relies on a novel hybrid dataflow model, combining aspects of both demand and data-driven execution.
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