Authors: Jie Deng, Yunxiang Li, Xiao Liang, Weiguo Lu, Jiacheng Xie, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas
Abstract Preview: Purpose: Recently, foundational models trained on large datasets have shown remarkable performance across various tasks. Developing a foundational model for medical image modality translation in head-...
Authors: Amir Abdollahi, Oliver Jäkel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome
Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH
Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...
Authors: Olivier Blasi, Eric Cameron, Brad K. Lofton
Affiliation: CAMP, Colorado Assn in Medical Phys (CAMP)
Abstract Preview: Purpose:
Magnetic Resonance (MR) imaging obtained from external centers for radiation therapy (RT) planning can suffer from suboptimal protocols and geometric distortions. These issues can require ...
Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, Ying Zhang, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas
Abstract Preview: Purpose: Accurate delineation of treatment targets and organs-at-risk is crucial for radiotherapy. Despite significant progress in artificial intelligence (AI)-based automatic segmentation tools, effi...
Authors: Steve B. Jiang, Mu-Han Lin, Dan Nguyen, Beiqian Qi, Daniel Yang, Ying Zhang
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Online adaptive radiotherapy (oART) is a resource-intensive workflow requiring significant time and effort required from clinicians, particularly for the online evaluation of plan quality....
Authors: Kimberly Chan, Anke Henning, Mahrshi Jani, Andrew Wright, Xinyu Zhang
Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center
Abstract Preview: Purpose: To evaluate the performance of multiple deep learning architectures for MRSI reconstruction and determine their effectiveness in maintaining high-resolution metabolite mapping while reducing ...
Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity
Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...
Authors: Avneesh Chhabra, Zhiyue J. Wang, Qing Yuan
Affiliation: University of Texas Southwestern Medical Center
Abstract Preview: Purpose: Magnetic susceptibility artifacts from dental arches and hardware often compromise MRI neurography of jaw and facial nerves. This study aims to characterize these artifacts and provide insigh...