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Home > IGCT > IGCT_WORKSHOPS

IGCT Workshops

IGCT Workshops

 

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.

Workshop: Interactive sessions targeted to engage attendees in discussions and activities designed to advance the program's goals

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  • The Importance of Reproducible Research in High-Throughput Biology by Keith Baggerly PhD

    The Importance of Reproducible Research in High-Throughput Biology

    December 12, 2024

    Keith Baggerly, PhD
    Professor, Department of Bioinformatics and Computational Biology, (retired)

  • Open Access, Public Good, and FAIR Science: Principles of the Effective Scientific Dissemination by C. Dave Fuller MD, PhD

    Open Access, Public Good, and FAIR Science: Principles of the Effective Scientific Dissemination

    August 24, 2023

    C. Dave Fuller, MD, PhD
    Professor, Department of Radiation Oncology at MD Anderson Cancer Center

  • Introduction to Medical Imaging & Radiology - Breast by Megan J. Kalambo MD

    Introduction to Medical Imaging & Radiology - Breast

    October 22, 2024

    Megan J. Kalambo, MD
    Associate Professor, Department of Breast Imaging at MD Anderson Cancer Center

  • Bayesian Clinical Trial Design Workshop by J. Jack Kee PhD, DDS; Ruitao Lin PhD; Suprateek Kundu PhD; and C. Dave Fuller MD, PhD

    Bayesian Clinical Trial Design Workshop

    September 16, 2024

    The Image Guided Cancer Therapy Research Program together with the CCSG Image-Driven Biology-Informed Therapy Program Workshop Series presents

    “Bayesian Clinical Trial Design Workshop”

    Session I: Clinical Trial Overview & Bayesian Basics
    J. Jack Lee, PhD, DDS, Professor of Biostatistics

    Session II: Bayesian Early-Phase Clinical Trial Designs
    Ruitao Lin, PhD, Assistant Professor of Biostatistics

    Session III: Analyzing Imaging Data for Implementation of Bayesian Approaches
    Suprateek Kundu, PhD, Associate Professor of Biostatistics

    Session IV: Running Bayesian Clinical Trials
    C. Dave Fuller, MD, PhD, Professor of Radiation Oncology

  • Innovations in MR-Linac Treatment – Physics Perspective by Eric Paulson PhD, Ergys Subashi PhD, Martin Fast, Daniel Hyer PhD, and Weiguo Lu PhD

    Innovations in MR-Linac Treatment – Physics Perspective

    July 23, 2023

    Session I: Strategies for Alternative Online Adaptation Workflows for Unity
    Eric Paulson, PhD
    Associate Professor, Radiation Oncology Medical, College of Wisconsin

    Implementation of Customized Imaging Sequences for MR-Guided Adaptive Radiotherapy in a High-Field MR-Linac
    Ergys Subashi, PhD
    Assistant Attending Physicist, Medical Physics Memorial Sloan Kettering Cancer Center

    MR-Linac Motion Management: Start of a New Dawn
    Martin Fast, PhD
    Associate Professor, Radiotherapy University Medical Center Utrecht

    Session II: Unity Treatment Planning Insights
    Daniel Hyer, PhD
    Professor, Radiation Oncology University of Iowa

    Online Adaptation Workflows QA
    Weiguo Lu, PhD
    Professor, Radiation Oncology UT Southwestern Medical Center

  • Human Brain Finite Element Mesh Generation from Patient MRI Data by Travis Thompson PhD

    Human Brain Finite Element Mesh Generation from Patient MRI Data

    March 6, 2023

    Travis Thompson, PhD
    Assistant Professor, Department of Mathematics & Statistics at Texas Tech University

    Part I: Motivation and an Introduction to the Software Pipeline

    Part II: Building Your First Finite Element Human Brain Mesh with the SVMTk

    Part III: Hands-On Mesh Generation Open Lab

  • GitHub Workshop by John Wood MS and Austin Castelo BS

    GitHub Workshop

    January 27, 2023

    John Wood, MS Senior Applications Systems Analyst, Enterprise Development and Integration, The University of Texas MD Anderson Cancer Center

    Austin Castelo, BS Associate Systems Analyst, Imaging Physics Department, The University of Texas MD Anderson Cancer Center

    Part I: GitHub Basics - for faculty, investigators, future, and active GitHub users

    Part II: Using Institutional GitHub – for active and future GitHub users

    Part III: GitHub Demo, Interactive Discussion, and Troubleshooting – for active and future GitHub users

 
 
 

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