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Results for "Hyejoo Kang": 5 found

Feasibility of Using a Convolutional Neural Network to Predict Physician Evaluation of Synthetic Medical Images

Authors: Sofia Beer, Menal Bhandari, Alec Block, Nader Darwish, Joseph Dingillo, Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Rajkumar Kettimuthu, Jason Patrick Luce, Ha Nguyen, John C. Roeske, George K. Thiruvathukal, Austin Yunker

Affiliation: Data Science and Learning Division, Argonne National Laboratory, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago, Department of Computer Science, Loyola University of Chicago

Abstract Preview: Purpose: Artificial intelligence (AI) generated synthetic medical images are seeing increased use in radiology and radiation oncology. Physician observer studies are an ideal way to evaluate the usabi...

Impact of Six Degrees of Freedom Intrafraction Motion on Target Coverage for Single-Isocenter Multi-Target Stereotactic Radiosurgery

Authors: Anupama Chundury, Hyejoo Kang, John C. Roeske, Iris A. Rusu

Affiliation: Loyola University Medical Center, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago

Abstract Preview: Purpose: To quantify the dosimetric impact of six degrees of freedom (6DoF) intrafractional errors on gross tumor volume (GTV) and planning target volumes (PTV) for single-isocenter multi-target stere...

Optimizing Low-Dose Imaging Parameters for Dual-Energy Cone-Beam Computed Tomography in Image-Guided Radiation Therapy

Authors: Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Luke Layman, Jason Patrick Luce, Ha Nguyen, John C. Roeske

Affiliation: Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago

Abstract Preview: Purpose:
This study aims to optimize virtual monoenergetic (VM) images obtained from dual-energy (DE) cone-beam computer tomography (CBCT) protocols for Image-Guided Radiation Therapy (IGRT). The o...

Qualitative Assessment of Low-Dose 4D Cone-Beam CT Protocols for Daily Lung SBRT Patient Alignment

Authors: Yussuf A. Abdelal, Junguo Bian, Michael Delafuente, Sebastien A. Gros, Hyejoo Kang, Luke Layman, M Mahesh, John C. Roeske

Affiliation: Department of Radiology and Medical Imaging, Stritch School of Medicine, Loyola University Medical Center, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Johns Hopkins Univ

Abstract Preview: Purpose: This study evaluates the feasibility of optimizing 4DCBCT imaging protocols for gated lung SBRT, by reducing dose while maintaining the image quality required for accurate patient alignment.<...

Quality Assurance Program for Dual Energy Subtraction Imaging-Based Markerless Tumor Tracking

Authors: Hyejoo Kang, Andrew Keeler, Mathias Lehmann, Jason Patrick Luce, Ha Nguyen, John C. Roeske

Affiliation: Varian Imaging Laboratory, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago

Abstract Preview: Purpose: Markerless tumor tracking (MTT) using dual-energy (DE) subtraction imaging is being considered as a non-invasive method to track tumors during lung cancer treatment. Prior to clinical impleme...