Medical imaging plays a crucial role in cancer detection, diagnosis, staging, treatment planning and therapy re- sponse monitoring. We propose to develop and disseminate a realistic X-ray-based Cancer Imaging Simulation Toolkit (XCIST). This toolkit could dramatically accelerate research related to cancer imaging and radiation dose reduction. This proposal builds on prior software development by three experienced teams with a long his- tory of collaboration. Drawing on each team's specific capabilities, we will create an integrated software toolkit hosted in an open-source environment. The toolkit will include GE Global Research's X-ray and CT imaging models and dose estimation models, Duke University's realistic digital representations of patients and tumors, and the University of Massachusetts Lowell's state-of-the-art image reconstruction implementations.
We will develop and disseminate an open-source, realistic X-ray-based Cancer Imaging Simulation Toolkit (XCIST), including X-ray and CT system models, realistic tumor phantoms, and state-of-the-art image recon- struction algorithms.
