Authors: Si-Wa Chan, Yuan-Yu Lee, Zhi-Ying Li, Jia-Wei Liao, Hui-Yu Cathy Tsai
Affiliation: Department of Radiology, Taichung Veterans General Hospital, Institute of Nuclear Engineering and Science, National Tsing Hua University
Abstract Preview: Purpose: Dense breast tissue reduces the sensitivity of mammography, posing diagnostic challenges, especially for Asian women with high breast density (up to 50%). Current single-modality techniques o...
Authors: Hui-Shan Jian, Yu-Ying Lin
Affiliation: Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou
Abstract Preview: Purpose: The image quality assurance of mammographic images is crucial for correct diagnosis. To develop and validate an explainable deep-learning classifier for phantom image quality assessment of di...
Authors: Hannah Grover, Andrew J. Sampson
Affiliation: Oregon Health & Science University, UT Health San Antonio
Abstract Preview: Purpose: The goal of this work was to quantify the dosimetric impact of iodinated contrast on fibroglandular breast tissue to better inform clinical risk and benefit assessments when determining the m...
Authors: Xuelian Chen, John Ginn, Zhuhong Li, Kaizhong Shi, Chunhao Wang, Jianliang Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao
Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University
Abstract Preview: Purpose: Developing deep learning-based models for accurate automated breast cancer diagnosis from mammography presents significant challenges due to the small size and subtle nature of breast lesions...
Authors: Jing-Tzyh Alan Chiang, Andrew Karellas, Thomas C Larsen, Hsin Wu Tseng, Srinivasan Vedantham
Affiliation: Department of Biomedical Engineering, The University of Arizona, Department of Medical Imaging, The University of Arizona
Abstract Preview: Purpose: To investigate the performance of dedicated breast computed tomography (BCT) for the the tasks of detection of soft tissue lesions and microcalcifications using cascaded systems analysis. The...
Authors: Xiaoyu Duan, Xiang Li, Wenbo Wan, Lei Zhang, Yiwen Zhang
Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Breast screening has been proved to reduce breast cancer mortality by early detection and treatment for patients. Mammography is the most common and widely used technique for breast cancer sc...
Authors: Alexander Bookbinder, Matthew Tivnan, Xiangyi Wu, Wei Zhao
Affiliation: Stony Brook Medicine, Massachusetts General Hospital
Abstract Preview: Purpose: To investigate and benchmark a system-adaptive diffusion-based digital breast tomosynthesis (DBT) denoising model for a direct-indirect dual-layer flat panel detector (DI-DLFPD) with a k-edge...
Authors: John M. Boone, Andrew M. Hernandez, Paul Schwoebel, Jeffrey H. Siewerdsen, Alejandro Sisniega, Wojciech B. Zbijewski
Affiliation: Johns Hopkins University, University of California, UT MD Anderson Cancer Center, University of New Mexico Albuquerque, UC Davis Health
Abstract Preview: Purpose: To significantly improve image quality relative to clinically deployed digital breast tomosynthesis (DBT) systems, which use a 1D acquisition geometry (an arc), with a 2D image acquisition ge...
Authors: Rodrigo T Massera, Sofia Giaccone Thomaz, Alessandra Tomal, Giovanna Tramontin
Affiliation: Universidade Estadual de Campinas. Instituto de Física Gleb Wataghin, Department of Imaging & Pathology, unit of Medical Physics & Quality Assessment, KU Leuven
Abstract Preview: Purpose: Monte Carlo simulations are increasingly used in breast dosimetry for their precision in estimating difficult-to-measure quantities, such as glandular dose. With ionizing radiation in breast ...
Authors: Melissa L. Hill
Affiliation: Volpara Health
Abstract Preview: N/A...
Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang
Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...
Authors: James Ward, Anzi Zhao
Affiliation: Northwestern Medicine
Abstract Preview: Purpose: This study investigates the impact of tissue-equivalent attenuator materials, the region of interest (ROI) size, and the orientation of the attenuator positioning on the measured signal-to-no...
Authors: Ahad Ollah Ezzati, Xiaoyu Hu, Xun Jia, Youfang Lai, Kai Yang, Yuncheng Zhong
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Massachusetts General Hospital, Johns Hopkins University
Abstract Preview: Purpose: Gantry motion and patient breathing during a breast cone beam CT (bCBCT) scan is one of the major challenges for microcalcification (μCalcs) detection. By deploying a large number of individu...
Authors: Ahad Ollah Ezzati, Xiaoyu Hu, Xun Jia, Youfang Lai, Kai Yang, Yuncheng Zhong
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Massachusetts General Hospital, Johns Hopkins University
Abstract Preview: Purpose: Contrast-enhanced breast cone-beam computed tomography (bCBCT) provides high-resolution, 3D imaging of breast tissues with improved differentiation between normal and abnormal tissues. Curren...
Authors: Peymon Ghazi
Affiliation: MALCOVA Inc.
Abstract Preview: Purpose: To develop a near scatter‐free breast CT imaging system that expands coverage of the posterior breast anatomy and enhances contrast resolution for solid masses and microcalcifications, while ...
Authors: Zahra Bagherpour, Manijeh Beigi, Pedram Fadavi, Faraz Kalantari, Moghadaseh Khaleghibizaki, Hengameh Nazari, Mojtaba Safari, Sepideh Soltani
Affiliation: Department of Radiation Oncology, School of Medicine, Iran University of Medical Sciences, Department of Radiation Oncology, School of Medicine, Emory University and Winship Cancer Institute, Department of Radiation Oncology, Iran University of Medical Sciences, University of Arkansas for medical sciences, Department of Radiation physics, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences
Abstract Preview: Purpose: This study aims to evaluate whether readily available mammographic and sonographic data, combined with machine learning (ML) models, can predict critical molecular factors (ER, PR, HER2) in b...
Authors: Jeffrey S. Nelson, Raj Kumar Panta, Megan K. Russ, Ehsan Samei
Affiliation: Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Contrast-enhanced mammography (CEM) enhances tumor detection by utilizing energy-dependent information from iodinated contrast agents. However, there is a lack of quantitative techniques to a...
Authors: Dimitrana Angelova, Gueorgui Gueorguiev, Kremena Ivanova, Filip Simeonov
Affiliation: National Centre of Radiobiology and Radiation Protection
Abstract Preview: Purpose: Mobile mammography screening programs focused on underprivileged populous in Bulgaria, such as the Romani people, are of great importance as such populations often don’t have access or are re...
Authors: Stephen Araujo, Jing-Tzyh Alan Chiang, Cynthia E. Davis, Eri Haneda, Andrew Karellas, Thomas C Larsen, William Ross, Hsin Wu Tseng, Srinivasan Vedantham, Pengwei Wu
Affiliation: Department of Biomedical Engineering, The University of Arizona, GE Aerospace Research, Department of Medical Imaging, The University of Arizona, GE HealthCare Technology & Innovation Center
Abstract Preview: Purpose: To determine the system parameters and technique factors for image acquisition needed so that the mean glandular dose (MGD) of approximately 4.5 mGy is not exceeded for a recently developed, ...