Stereotactic Radiosurgery (SRS) of asymptomatic brain metastases provides lasting tumor control with only minor side effects to healthy brain. An active research area is the development of models to predict tumor response to a given dose of Radiation Treatment (RT) from analysis of pre-RT and post-RT MR images (i.e., the forward problem). Here we propose an approach to train a deep neural net on pre-RT MR images of patients with Breast Cancer Metastases to the Brain (BCMB), for predicting RT dose maps that will yield desired/target tumor voxel intensities on post-RT MR images (i.e., the inverse problem).
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