Chih-Wei Chang
Overview
Chih-Wei Chang, PhD, is an assistant professor and medical physicist in the Department of Radiation Oncology at Emory University School of Medicine.
Dr. Chang earned his PhD in nuclear engineering at North Carolina State University in Raleigh, North Carolina. He obtained his MS and BS in nuclear engineering and engineering and system science at the National Tsing Hua University in Hsinchu, Taiwan. He completed his medical physics residency with the Department of Radiation Oncology at Emory University School of Medicine in Atlanta, Georgia.
Dr. Chang's research interests include multidisciplinary approaches integrating state-of-the-art techniques, especially AI, to solve real-world challenges for radiation oncology and medical physics using GAI, physics-informed machine learning, digital-twin for online adaptive radiotherapy, and LLM-based clinical safety decision-making. He has been instrumental in formulating the physics-informed machine learning framework for nuclear system thermal-hydraulic simulation using partial differential equations. During his medical physics residency training at Emory University, He adapted this data-driven framework to enable CT-material characterization to improve proton range uncertainty and unsupervised deep learning-based CT metal artifact reduction.
Dr. Chang also devised a standardized commissioning framework for Monte Carlo-based treatment planning systems, which he applied to assess beam model uncertainties attributed to vendor upgrades and CT stoichiometric calibrations at Emory. This framework was also adopted by AAPM Task Group No. 349 - Commissioning of Monte Carlo Dose Calculation in Proton Therapy.
Academic Appointment
- Assistant Professor, Department of Radiation Oncology, Emory University School of Medicine
Education
Degrees
- PhD from North Carolina State University
- MS from National Tsing Hua University
- BS from National Tsing Hua University
Research
Publications
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Data-Driven Volumetric Computed Tomography Image Generation From Surface Structures Using a Patient-Specific Deep Leaning Model.
Int J Radiat Oncol Biol Phys Volume: 121 Page(s): 1349 - 1360
04/01/2025 Authors: Pan S; Chang C-W; Tian Z; Wang T; Axente M; Shelton J; Liu T; Roper J; Yang X -
Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging
03/10/2025 Authors: Yang X; Wang S; Safari M; Li Q; Chang C-W; Qiu R; Roper J; Yu D -
Exploration of an adaptive proton therapy strategy using CBCT with the concept of digital twins.
Phys Med Biol Volume: 70
01/17/2025 Authors: Chang C-W; Tian Z; Qiu RLJ; Scott Mcginnis H; Bohannon D; Patel P; Wang Y; Yu DS; Patel SA; Zhou J -
Using a patient-specific diffusion model to generate CBCT-based synthetic CTs for CBCT-guided adaptive radiotherapy.
Med Phys Volume: 52 Page(s): 471 - 480
01/01/2025 Authors: Chen X; Qiu RLJ; Wang T; Chang C-W; Chen X; Shelton JW; Kesarwala AH; Yang X -
Unsupervised Bayesian generation of synthetic CT from CBCT using patient-specific score-based prior.
Med Phys
12/12/2024 Authors: Peng J; Gao Y; Chang C-W; Qiu R; Wang T; Kesarwala A; Yang K; Scott J; Yu D; Yang X -
CBCT-based synthetic CT image generation using a diffusion model for CBCT-guided lung radiotherapy.
Med Phys Volume: 51 Page(s): 8168 - 8178
11/01/2024 Authors: Chen X; Qiu RLJ; Peng J; Shelton JW; Chang C-W; Yang X; Kesarwala AH -
Deep Learning-Based Fast Volumetric Image Generation for Image-Guided Proton Radiotherapy
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES Volume: 8 Page(s): 973 - 983
11/01/2024 Authors: Chang C-W; Lei Y; Wang T; Tian S; Roper J; Lin L; Bradley J; Liu T; Zhou J; Yang X -
Artificial intelligence-based motion tracking in cancer radiotherapy: A review.
J Appl Clin Med Phys Volume: 25 Page(s): e14500
11/01/2024 Authors: Salari E; Wang J; Wynne JF; Chang C-W; Wu Y; Yang X -
Exploring dual energy CT synthesis in CBCT-based adaptive radiotherapy and proton therapy: application of denoising diffusion probabilistic models.
Phys Med Biol Volume: 69
10/18/2024 Authors: Viar-Hernandez D; Manuel Molina-Maza J; Pan S; Salari E; Chang C-W; Eidex Z; Zhou J; Antonio Vera-Sanchez J; Rodriguez-Vila B; Malpica N -
An LLM-Based Framework for Zero-Shot De-Identifying Flexible Text Data in Protected Health Information Enabling Potential Risk-Informed Patient Safety
Volume: 120 Page(s): E518 - E518
10/01/2024 Authors: Chang CW; Hu M; Ghavidel B; Wynne JF; Qiu RLJ; Washington M; Kayode O; Chin WG; Yang K; Scott JG