David A. Hormuth, II

Research Scientist | Biomedical Engineering + Imaging Science > > Computational Oncology


Forecasting response of high-grade glioma patients to radiation therapy

The focus of this project is to translate our efforts at the pre-clinical level to the clinical setting. The longterm vision is to improve patient outcomes through the use of accurate predictive models personalized for each patient

Image-driven models of tumor growth in the pre-clinical setting

While not perfect, the pre-clinical setting is a great area to explore optimal ways to incorporate different imaging (MRI, PET, microscopy, etc) with mathematical models of tumor growth and response.

Repeatable & reproducible cancer imaging methods

Repeatable and reproducible approaches for acquiring and analyzing images is crucial for clinical decision making and for inclusion in mathematical models.


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