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Results for "Andrew Keeler": 3 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...

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...

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...