Balter Lab Research

Our lab investigates the development of patient models that support both the planning of radiation therapy as well as image-guided patient positioning. Patient models are derived from a combination of the intensity patterns of different tissues across different MRI contrasts, as well as through the integration of prior knowledge of anatomic shapes (e.g. pelvic bones) within a population of patients. Synthetic CT models of the head have been developed and clinical implementation is expanding from initial support of whole-brain radiotherapy to more focal treatments of glioblastomas and stereotactic treatments of multiple metastases.

MR imaging is typically slow and subject to artifacts from several factors that limit its utility for supporting a number of radiation therapy tasks, including target definition and understanding and reacting to motion.  Fortunately, sufficient sparsity exists to potentially support these tasks with more efficient sampling and/or intelligent reconstruction techniques. Our lab is currently investigating sparsity of patient body shapes and physiological motions.

MR imaging is typically slow and subject to artifacts from several factors that limit its utility for supporting a number of radiation therapy tasks, including target definition and understanding and reacting to motion.  Fortunately, sufficient sparsity exists to potentially support these tasks with more efficient sampling and/or intelligent reconstruction techniques. Our lab is currently investigating sparsity of biological mapping of diffusion, morphological mapping of anatomic structure, and mapping hierarchical motion states of patients.

MR imaging is typically slow and subject to artifacts from several factors that limit its utility for supporting a number of radiation therapy tasks, including target definition and understanding and reacting to motion.  Fortunately, sufficient sparsity exists to potentially support these tasks with more efficient sampling and/or intelligent reconstruction techniques. Our lab is currently investigating sparsity of biological mapping of diffusion, morphological mapping of anatomic structure, and mapping hierarchical motion states of patients.