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IGCT Seminars

IGCT Seminars

 

The Image Guided Cancer Therapy (IGCT) Research Program empowers multidisciplinary teams of physicians and scientists to address the clinical challenges and technology barriers using resources of the program to drive the translation of innovative science directly to patient care.

Seminar: Sessions designed to discuss scientific advancements in image guided cancer therapy

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  • Mathematical Modeling of Biological Systems for Oncology Applications: From Basic Science to Clinically Translatable Methods by Joseph D. Butner PhD

    Mathematical Modeling of Biological Systems for Oncology Applications: From Basic Science to Clinically Translatable Methods

    April 13, 2023

    Joseph D. Butner, PhD
    Faculty Fellow, Mathematics in Medicine Program at Research Institute at Houston Methodist

  • Exploring New Treatment Planning Paradigms Using Machine Learning by Thomas G. Purdie PhD

    Exploring New Treatment Planning Paradigms Using Machine Learning

    February 24, 2023

    Thomas G. Purdie PhD
    Associate Professor, Departments of Radiation Oncology and Medical Biophysics at University of Toronto; Medical Physicist, Princess Margaret Cancer Centre - University Health Network

  • At the Intersection of AI and Ethics: How do we Engage the Public? by Jodyn E. Platt MPH, PhD

    At the Intersection of AI and Ethics: How do we Engage the Public?

    December 07, 2022

    Jodyn E. Platt, MPH, PhD
    Associate Professor, Learning Health Sciences at University of Michigan Medical School

  • Radiation-Therapy Related Cardiac Disease in Childhood Cancer Survivors by Rebecca Howell PhD

    Radiation-Therapy Related Cardiac Disease in Childhood Cancer Survivors

    November 18, 2022

    Rebecca Howell, PhD
    Professor, Radiation Physics; Director, Medical Physics Graduate Program at MD Anderson Cancer Center

  • Image-Guided, Robot-Assisted Surgery: From High-Precision to High-Reliability by Jeffrey H. Siewerdsen PhD

    Image-Guided, Robot-Assisted Surgery: From High-Precision to High-Reliability

    October 19, 2022

    Jeffrey H. Siewerdsen, PhD
    Professor, Departments of Imaging Physics, Neurosurgery, and Radiation Physics; Director of the Surgical Data Science Program, Institute for Data Science in Oncology (IDSO) at MD Anderson Cancer Center

  • Identifying Imaging Features that Predict Radiation Therapy Response in a Preclinical Setting by Tien T. Tang PhD

    Identifying Imaging Features that Predict Radiation Therapy Response in a Preclinical Setting

    September 13, 2022

    Tien T. Tang, PhD
    Postdoctoral Associate, Department of Pediatrics at Baylor College of Medicine

  • Anatomical Modeling to Improve the Precision of Image Guided Liver Ablation: A COVER-ALL Clinical Trial Update by Caleb O'Connor MS, Yung-Mao (Gary) Lin MD, Iwan Paolucci PhD, and Bruno C. Odisio MD

    Anatomical Modeling to Improve the Precision of Image Guided Liver Ablation: A COVER-ALL Clinical Trial Update

    June 01, 2022

    Caleb O’Connor, MS
    Medical Physics Assistant, Department of Imaging Physics at MD Anderson Cancer Center

    Yuan-Mao (Gary) Lin, MD
    Postdoctoral Fellow, Department of Interventional Radiology at MD Anderson Cancer Center

    Iwan Paolucci, PhD
    Postdoctoral Fellow, Department of Interventional Radiology at MD Anderson Cancer Center

    Bruno C. Odisio, MD
    Associate Professor, Department of Interventional Radiology at MD Anderson Cancer Center

 
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