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: Weiguo Lu, Hua-Chieh Shao, Guoping Xu, 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
Abstract Preview: Purpose:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...
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: Hailun Pan, Yingli Yang, Jie Zhang, Yibin Zhang
Affiliation: Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital, Department of Radiation Oncology, Ruijin Hospital, , Shanghai Jiaotong University School Of Medicine, Shanghai United imaging Healthcare Advanced Technology Research Institute
Abstract Preview: Purpose: Accurate patient positioning is critical in radiotherapy (RT) to ensure effective treatment delivery and minimize harming surrounding healthy tissues. Vertebral misalignment during RT setup h...
Authors: Yifei Hao, Wenxuan Li, Xiang Li, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Yaogong Zhang
Affiliation: Duke University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Diffusion-based deep-learning frameworks have been recently used in MRI resolution enhancement, or super-resolution. Multi-contrast MRI share common anatomical structures while holding comple...
Authors: Debarghya China, Junghoon Lee, Ali Uneri
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins Univ
Abstract Preview: Purpose: This study aims to develop a population-based cardio-respiratory motion model and apply it to patient-specific 3D CTA to simulate 4D CTA and 2D+t fluoroscopy sequences. The developed motion m...
Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia
Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio
Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...
Authors: Kota Hirose, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami
Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University
Abstract Preview: Purpose: Synthesizing medical images can address the lack of or unscanned medical images, reducing scanner time and costs. However, paired image scarcity remains a challenge for image synthesis. We pr...
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: Ahmad Algohary, Adrian Breto, Quadre Emery, Radka Stoyanova
Affiliation: University of Miami, Department of Radiation Oncology, University of Miami
Abstract Preview: Purpose:
To develop a foundation model (U-Found) for multiparametric MRI (mpMRI) of the prostate by using self-supervised learning to prove the feasibility of a prostate-oriented foundation model u...
Authors: David Ayala Alvarez, Facundo Ballester, Luc Beaulieu, Francisco Berumen-Murillo, Jean-Simon Cote, Ernesto Mainegra-Hing, Iymad Mansour, Gaël Ndoutoume-Paquet, Rowan M. Thomson, Christian Valdes, Javier Vijande, Peter G. Watson
Affiliation: Département de physique, de génie physique et d'optique, Université Laval, Laval University, Princess Margaret Cancer Centre, McGill University, Department of Physics and Medical Physics Unit, McGill University, IFIC-UV, University of Valencia, National Research Council Canada, Carleton University, 5Service de Physique Médicale et de Radioprotection, Centre Intégré de Cancérologie, CHU de Québec- Université Laval et Centre de recherche du CHU de Québec, Nuclear Medicine Department, Hospital Regional de Antofagasta
Abstract Preview: Purpose: Modelling electronic brachytherapy (eBT) sources is difficult because of the high-dose gradients and challenges associated with low-energy modelling. This study examines the accuracy of avail...
Authors: Bryan Bednarz, John M. Floberg, Joseph B. Schulz, Jordan M. Slagowski
Affiliation: Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Department of Radiation Oncology, Stanford University School of Medicine, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: Catheter placement for high-dose-rate brachytherapy (HDR BT) is clinician dependent and potentially suboptimal for delivering simultaneous integrated boosts to intraprostatic gross tumor volu...
Authors: Xuezhen Feng, Li-Sheng Geng, Haoze Li, Xi Liu, Tianyu Xiong, Ruijie Yang
Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, School of Physics, Beihang University, School of Nuclear Science and Technology, University of South China, Department of Radiation Oncology, Peking University Third Hospital
Abstract Preview: Purpose: This study aimed to develop a deep learning-based algorithm for automatically delineate gross tumor volume (GTV) for lung cancer patients, alleviating the workload of radiologists and improvi...
Authors: Guha Balakrishnan, Osama R. Mawlawi, Yiran Sun, Ashok Veeraraghavan
Affiliation: RICE University, UT MD Anderson Cancer Center
Abstract Preview: Purpose:
Previous deep learning (DL) techniques such as X2CT-GAN [1] has shown great promise in reconstructing realistic CT volume from biplanar X-rays, however they introduce numerous artifacts in...
Authors: Wesley S. Culberson, Albert Du, Ryan T. Flynn, Alonso N. Gutierrez, Patrick M Hill, Daniel E. Hyer, Kaustubh A. Patwardhan, Blake R. Smith, Nhan Vu, Karsten K. Wake
Affiliation: University of Wisconsin, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Miami Cancer Institute, Baptist Health South Florida, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, University of Iowa, Iowa Health Care
Abstract Preview: Purpose:
To perform end-to-end treatment planning and delivery verification of energy-specific collimated treatments optimized to achieve the maximum obtainable high-dose conformity using the dynam...
Authors: Ziqi Gao, Lei Xing, Siqi Ye, S. Kevin Zhou
Affiliation: Department of Radiation Oncology, Stanford University, University of Science and Technology of China (USTC)
Abstract Preview: Purpose: To address the challenge of high memory usage in volumetric cone-beam CT (CBCT) imaging, we propose a method that combines joint reconstruction and super-resolution for sparsely sampled CBCT ...
Authors: Yifei Hao, Chengliang Jin, Wenxuan Li, Bing Luo, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Ruojun Zhou
Affiliation: School of Future Science and Engineering, Soochow University, Electrical and Computer Engineering Graduate Program, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Federated learning is a patient privacy-protecting technique that has recently been applied in the medical field. This study aims to evaluate the performance of several deep learning networks...
Authors: Chih-Chiang Chang, Chingyun Cheng, Ben Durkee, Minglei Kang, Elissa Khoudary, Yangguang Ma, Xuanqin Mou, YuFei Wang, Tengda Zhang, Wang Zhengda
Affiliation: Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Department of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, School of Software Engineering, Xi’an Jiaotong University, School of information and communications engineering, Faculty of electronic and information engineering, Xi’an Jiaotong University, Department of Medical Physics, Columbia University, University of Pennsylvania, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: This study presents a voxel-based analysis method based on deformable image registration to accurately quantify respiratory-induced motion and deformation of both targets and organs at risk (...
Authors: Trevor McKeown, Deshan Yang, Zhendong Zhang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: Accurate delineation of liver blood vascular structures is crucial for planning and executing therapeutic interventions in liver-related medical procedures. However, current auto-segmentation...