Authors: Matthew S Brown, Joshua Genender, John M. Hoffman, Gabriel Melendez-Corres, Muhammad W. Wahi-Anwar
Affiliation: David Geffen School of Medicine at UCLA, UCLA Department of Radiology
Abstract Preview: Purpose: Renal lesions are evaluated using scoring systems based on visual assessments and manual measurements. The purpose of this work is to develop a multi-agent system for automated anatomic landm...
Authors: Jiayun Chen, Shengqi Chen, Yuan Tang, Zilin Wang, Guohua Wu, Jianan Wu
Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Abstract Preview: Purpose:
To develop a novel no-reference image quality assessment (NRIQA) method for evaluating the effectiveness of image preprocessing in MRI-guided radiotherapy (MRIgRT), thereby enhancing clini...
Authors: Shanli Ding, Osama R. Mawlawi, Tinsu Pan
Affiliation: UT MD Anderson Cancer Center
Abstract Preview: Purpose:
Reliable detection of anomalies in Gamma Camera/SPECT flood images is vital for quality assurance (QA). Traditional methods relying on numerical thresholds and manual inspections often mis...
Authors: Zilei Fu, Yi Guo, Wanli Huo, Hongdong Liu, Laishui Lyu, Zhao Peng, Yaping Qi, Senting Wang
Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University
Abstract Preview: Purpose: Medical image boundaries are commonly characterized by smooth gray-level transitions, resulting in pixel-level segmentation errors near these blurred boundaries. To address this, we developed...
Authors: Jean Bourbeau, Jim Hogg, Miranda Kirby, Meghan Koo, Kalysta Makimoto, Wan Tan
Affiliation: Montreal Chest Institute of the Royal Victoria Hospital, McGill University Health Centre, Toronto Metropolitan University, Centre for Heart Lung Innovation, University of British Columbia
Abstract Preview: Purpose: Chronic obstructive pulmonary disease (COPD) exacerbations are burdensome to patients and healthcare systems. CT imaging-derived measures of emphysema and airway remodeling have been shown to...
Authors: Justus Adamson, Mu Chen, Ke Lu, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Yaogong Zhang, Haipeng Zhao, Haiming Zhu, Yuchun Zhu
Affiliation: Shanghai Dacheng Medical Technology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: In filtered back-projection (FBP) reconstruction, conventional filters often reduce noise at the expense of high-frequency details, leading to structural details loss. To address this limitat...
Authors: Pradeep Bhetwal, Yingxuan Chen, Wookjin Choi, Michael Dichmann, Adam Dicker, Rupesh Ghimire, Yevgeniy Vinogradskiy, Maria Werner-Wasik
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Radiomics has emerged as a powerful tool in medical research. However, the lack of standardized and reproducible pipelines limits its clinical adoption. This study developed a robust and scal...
Authors: John Kildea, Odette Rios-Ibacache, Amal Zouaq
Affiliation: McGill University, Polytechnique Montréal
Abstract Preview: Purpose:
Even though Electronic medical records (EHRs) are now in widespread use in healthcare, and Artificial Intelligence tools incorporating radiomics are used to identify tumors in medical imag...
Authors: Jing Cai, Zhi Chen, Hong Ge, Yu-Hua Huang, Bing Li, Zihan Li, Ge Ren
Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital
Abstract Preview: Purpose: Algorithms based on subregional respiratory dynamics (SRD) capture spatiotemporal heterogeneity in the ventilation process, though rely on empirical modelings to map surrogate ventilation. Gi...
Authors: Taman Upadhaya
Affiliation: Cedars-Sinai Medical Center
Abstract Preview: N/A...
Authors: Xiaoda Cong, Xuanfeng Ding, Gang Liu, Peilin Liu, Jiajian Shen
Affiliation: Department of Radiation Oncology, Mayo Clinic, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Corewellhealth William Beaumont University Hospital
Abstract Preview: Purpose: This study aims to develop the first SPArc optimization algorithm based on the Dynamic Programming (SPArc-DP), to improve the treatment delivery efficiency for synchrotron-accelerator-based P...
Authors: Hyosung Cho, Dae Yup Han, Duhee Jeon, Jiwon Park, Hyesun Yang
Affiliation: Department of Therapeutic Radiology, Yale University School of Medicine, Yonsei University
Abstract Preview: Purpose: Scatter in X-ray imaging degrades image quality, hindering the visibility of critical anatomical features and complicating patient alignment in radiation therapy. This study aims to improve s...
Authors: Manju Liu, Ning Wen, Fuhua Yan, Yanzhao Yang, Zhenyu Yang, Haoran Zhang, Lei Zhang, Yajiao Zhang
Affiliation: Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy where precise segmentation of tumors and adjacent vessels is crucial for effective treatment planning. This study dev...
Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu
Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles
Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...