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    • PI: E. Castillo
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Edward Castillo, PhD

Edward Castillo (he/him/his) is the principal investigator and director of the Dynamic Medical Image and Computing Lab. He is an Associate Professor of Biomedical Engineering at UT Austin and an Adjunct Associate Professor of Computational and Applied Mathematics (CAAM) at Rice University. He received his Bachelor of Science in mathematics from St. Mary’s University in San Antonio, TX and was a graduate of the University’s Honors Program. After receiving his PhD in CAAM from Rice University, Dr. Castillo completed a post-doctoral fellowship in Mathematics at the University of California, Irvine. Prior to joining the UT BME faculty, Dr. Castillo was an Assistant Professor of Radiation Physics at UT MD Anderson Cancer Center (2009-2014) and an Associate Professor of Radiation Oncology at the Oakland University William Beaumont School of Medicine (2014-2021).

Dr. Castillo’s research program is focused on the theoretical development, implementation, and clinical application of numerical methods for medical image analysis. In collaboration with medical physicists, he has pioneered computational methods for inferring patient-specific functional tissue properties from dynamic medical imaging. Dr. Castillo and his clinical collaborators have demonstrated that incorporating these methods into the treatment planning process significantly improves radiotherapy outcomes for lung cancer patients. Dr. Castillo has been awarded several grants including an NIH/NCI Academic-Industry Partnership R01 and an NIH/NCI Quantitative Imaging Network UG3. He is a Charter Member for the Image Guided Intervention and Surgery (IGIS) study section of the NIH, a member of the Society for Industrial and Applied Mathematics (SIAM), and a member of the American Association of Physicists in Medicine (AAPM). Dr. Castillo is also an Affiliated Faculty Member of the Oden Institute.

edward.castillo@utexas.edu

Primary Sidebar

The DMIC Lab has been awarded a Computational Oncology Grant to develop models to forecast the lung's functional response to cancer radiotherapy.

The DMIC Lab and 4D Medical are collaborating on a sponsored research project to further develop image processing methods for quantifying lung health.

Dynamic Lung Compliance Imaging Method published in PMB

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