Nearly every field of biomedical research relies on organ-scale simulation as a research component, and in most such fields there is a recognition that geometry is profoundly important. Yet, there is still a technologically weak link between medical imaging and modeling generation and simulation, specifically the enabling technologies in computational geometry for processing image-derived biological geometries. Where such tools are available they typically require a programming ability beyond the ken of most practitioners, particularly students. We have developed and continue to develop an interoperative toolkit, called BioGeom.

Currently, the toolkit combines our own state-of-the-art computational geometry algorithms for generating, managing and analyzing geometries from biomedical images with leading open-source components in an easy-to-use and easy-to-program MATLAB/Octave-based framework. Modules created in BioGeom are easily converted to portable ANSI C, and therefore easily linked to external software applications or toolkits, such as Python or SciPy. In addition, Octave is an open-source clone of MATLAB, and thus freely available to all. The toolkit is designed to bridge the gap between medical imaging and modeling and simulation, by empowering biomedical practitioners, including students, to apply or create solutions tailored to their research needs.