Authors: Lorenzo Arsini, Andrea Ciardiello, Fabio Massimo D'Amore, Stefano Giagu, Federico Giove, Carlo Mancini-Terracciano, Cecilia Voena
Affiliation: Istituto Superiore di Sanità, Sapienza University of Rome, Università Sapienza Roma, Magnetic Resonance for Brain Investigation Laboratory, Museo Storico della Fisica e Centro di Studi e Ricerche Enrico Fermi
Abstract Preview: Purpose: To leverage newly developed heteronuclear magnetic resonance imaging (MRI) techniques, particularly sodium (23Na) imaging, for identifying potential biomarkers of Alzheimer's disease—such as ...
Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Bohong Huang, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Huiqiao Xie, Hao Zhang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Four-dimensional cone-beam computed tomography (4D-CBCT) is critical in image-guided radiotherapy (IGRT) for visualizing tumor motion. However, sparse projection sampling often introduces sev...
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: 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: Louis Archambault, Luc Beaulieu, Alexis Horik, Sajjad Ahmad Khan
Affiliation: Département de Physique, de Génie Physique et D'optique, et Centre de Recherche sur le Cancer, Université Laval, Département de physique, de génie physique et d'optique, Université Laval
Abstract Preview: Purpose: This study presents a novel 2D scintillation dosimeter leveraging long scintillating fibers for quality assurance (QA) in radiotherapy. The primary goal is to optimize critical parameters suc...
Authors: Chuan He, Anh H. Le, Iris Z. Wang
Affiliation: Roswell Park Comprehensive Cancer Center, Cedars-Sinai
Abstract Preview: Purpose: To develop a non-measured and DVH-based (NMDB) IMRT QA framework integrating machine learning (ML) to classify lung SBRT VMAT plans prone to delivery errors
Methods: 560 Eclipse AcurosXB l...
Authors: Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu, Jie Zhang
Affiliation: University of Maryland School of Medicine, University of California, Irvine
Abstract Preview: Purpose: To achieve the full-view image from a single-view sinogram using a two-stage deep learning model for electroacoustic-tomography (EAT), which is an emerging imaging technique with significant ...
Authors: Xiangli Cui, Man Hu, Wanli Huo, Da Yao, Jianguang Zhang, Yingying Zhang, Shanyang Zhao
Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences
Abstract Preview: Purpose:
To study the fine-tuning strategy of pre-trained AI image generation model to adapt to the generation of small sample meningioma MRI images, explore its impact on observer performance, and...
Authors: Zachary Buchwald, Zach Eidex, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu
Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Gadolinium-based contrast agents (GBCA) are commonly used for patients with gliomas to delineate and characterize the brain tumors using T1-weighted (T1W) MRI. However, there is a rising conc...
Authors: Yunxiang Li, Xinlong 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) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose: Acquiring high-resolution (HR) proton density (PD) images is time-consuming, while lower-resolution (LR) PD scans are faster but can lack sufficient details. We propose CycleHR, a T2-contrast...
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: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Richard L.J. Qiu, Mojtaba Safari, Shansong Wang, Xiaofeng Yang, David Yu
Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: MRI offers excellent soft tissue contrast for diagnosis and treatment but suffers from long acquisition times, causing patient discomfort and motion artifacts. To accelerate MRI, supervised d...
Authors: Jeremy Christophel, Zhihua Qi
Affiliation: Henry Ford Health
Abstract Preview: Purpose: To demonstrate a method to compare DICOM metadata from clinical scanners with institutional protocols as validation that clinical use matches the master protocol.
Methods: DICOM metadata i...
Authors: Hongyi Jiang, Fang-Fang Yin
Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose:
Imaging moving tissues using PET-CT can be difficult. Separating signal into phases during construction reduces signal count and increases influence of noise. Algorithms that use signal fr...
Authors: Matthew R. Hoerner, Maryam Naseri, Mena Shenouda
Affiliation: Yale University School of Medicine, Yale University
Abstract Preview: Purpose: To evaluate acquisition parameters of computed tomography (CT) scanner protocols across different machines to provide patients and clinicians consistent care and image quality, respectively.<...
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: Stephen Bhagroo, Sorour Hosseini, YuHuei Jessica Huang, Jeremy Kunz, Thomas Boyd Martin, Geoffrey S. Nelson, Nicholas Pierre Nelson, Ryan G. Price, Hui Zhao
Affiliation: University of Utah, Department of Radiation Oncology, Huntsman Cancer Institute, University of Utah
Abstract Preview: Purpose: To investigate the correlation between HyperSight CBCT imaging dose and image quality.
Methods: Six-series of 174 CBCT scans were acquired using HyperSight on Halcyon (125kV, 133-971mAs, F...
Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap
Affiliation: University of North Carolina at Chapel Hill, Huaqiao University
Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...
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: Beth Bradshaw Ghavidel, Chih-Wei Chang, Yuan Gao, Priyanka Kapoor, Shaoyan Pan, Junbo Peng, Richard L.J. Qiu, Jill Remick, Justin R. Roper, Zhen Tian, Xiaofeng Yang
Affiliation: Whinship Cancer Institute, Emory University, Emory University, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Current cone-beam computed tomography (CBCT) typically requires no less than 200 degrees of angular projections, which prolongs scanning time and increases radiation exposure. To address thes...
Authors: Guang-Pei Chen, Nitish Chopra, Juan A. Garcia-Alvarez, Mi Huang, Slade J. Klawikowski, Haidy G. Nasief, George A. Noid, Abdul Parchur, Eric S. Paulson, Christina M. Sarosiek, Christopher Schultz
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: During routine delivery of mask-based Gamma Knife (GK) SRS, motion is tracked via the position of a reflective sticker placed on the patient’s nose relative to two stationary reflectors on th...
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: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu
Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences
Abstract Preview: Purpose: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...
Authors: Ehsan Abadi, Njood Alsaihati, Steven T. Bache, Mridul Bhattarai, Cindy Marie McCabe, Francesco Ria, Ehsan Samei
Affiliation: Duke University, Center for Virtual Imaging Trials, Duke University, Duke University Health System, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: To compare and contrast alternative methods including reader (in hominum), phantom (in phantasma), in vivo, and in silico methods deployed to assess the performance of photon counting (PCCT) ...
Authors: Lei Ren, Jie Zhang
Affiliation: University of Maryland School of Medicine
Abstract Preview: Purpose: 4D-CBCT is valuable for imaging anatomy affected by respiratory motions to guide radiotherapy delivery. However, 4D-CBCT often has undersampled projections acquired in each respiratory phase ...
Authors: Rashmi Bhaskara, Oluwaseyi Oderinde
Affiliation: Purdue University
Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...
Authors: Mengqi Shen, Meghna Trivedi, Tony J.C. Wang, Andy (Yuanguang) Xu, Yading Yuan
Affiliation: Columbia University Medical Center, Dept of Med Hematology & Oncology, Data Science Institute at Columbia University, Columbia University Irving Medical Center, Department of Radiation Oncology, Columbia University Irving Medical Center
Abstract Preview: Purpose: T2-weighted (T2w) images are critical for identifying pathological changes due to their superior contrast in differentiating tissue types. However, they often lack detailed anatomical resolut...
Authors: Nan Li, Yaoying Liu, Shouping Xu, Xinlei Xu, Gaolong Zhang
Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, School of physics, Beihang University, Beihang University, Department of Radiation Oncology
Abstract Preview: Purpose:
CT simulation is essential for radiation therapy preparation but has limitations in distinguishing lesions. Contrast-enhanced CT (CECT) improves lesion detection and characterization, but ...
Authors: Kwang-Ho Cheong, Seungryong Cho, Joonil Hwang, Jae Won Jung, Hoyeon Lee, Raymond Hyunwoo Moon, Inhwan Yeo, Jihyung Yoon
Affiliation: East Carolina University, INOVA Schar Cancer Institute, University of Hong Kong, Hanllym University, KAIST, University of Rochester
Abstract Preview: Purpose: Monitoring a target and neighboring organs during beam delivery is crucial for successful radiotherapy (RT). Conventional transit imaging methods lack volumetric reconstruction capabilities, ...
Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Hui Mao, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu
Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, Emory University School of Medicine
Abstract Preview: Purpose: MRI-guided radiation therapy (MRgRT) benefits significantly from enhanced soft-tissue contrast and spatial resolution, which aid in accurately delineating tumors and organs at risk. Although ...
Authors: Nan Li, Shouping Xu, Gaolong Zhang, Xuerong Zhang
Affiliation: Department of Radiation Oncology, HeBei YiZhou proton center, School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Abstract Preview: Purpose:
The 3D BRAVO sequence is an advanced magnetic resonance (MR) technique that allows for image reconstruction at any angle. It offers 1 mm gapless scanning and has a high signal-to-noise rat...
Authors: Oluyemi Bright Aboyewa, KyungPyo Hong, Daniel Kim
Affiliation: Department of Radiology, Northwestern University
Abstract Preview: Purpose: While non-Cartesian MRI is desirable for fast imaging with high spatial resolution and robustness to motion, it requires long post-processing times. Preconditioning with an adequate density c...
Authors: Manju Liu, Weiwei Sang, Yanyan Shi, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lihua Zhang, Rihui Zhang
Affiliation: Jiahui International Hospital, Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to transform cone-beam computed tomography (CBCT) images acquired from deep inspiration breath-hold (DIBH) breast cancer patients into high-fidelity synthetic CT (sCT) images....
Authors: Kofi M. Deh, Tamas Jozsa, Tsang-Wei Tu
Affiliation: Cranfield University, Howard University Hospital, Howard University
Abstract Preview: Purpose: To enhance the quality of hyperpolarized (HP) 13C magnetic resonance images by integrating deep learning with perfusion modeling.
Methods: A convolutional neural network (CNN) and a superr...
Authors: Xinhua Li, Jie Zhang, Yifang (Jimmy) Zhou
Affiliation: University of Kentucky, Cedars-Sinai Medical Center
Abstract Preview: Purpose: Fat volume fraction (FVF) is an important biomarker for non-alcoholic fatty liver disease. CT can be a good modality for FVF assessment if the accuracy is adequate. We aimed to study the impa...
Authors: Samuel L. Brady, Kevin Chen, Joseph G. Meier
Affiliation: University of Cincinnati, Cincinnati Childrens Hospital Med Ctr
Abstract Preview: Purpose: Conebeam-CT (CBCT) acquisition protocols typically do not distinguish between adults and pediatrics. In collaboration with a fluoroscopically-guided interventional (FGI) manufacturer, new, do...
Authors: Mahya Ahmadzadeh, Nagarajan Kandasamy, Keyur Shah, Gregory C. Sharp, Santhosh Vadivel, John MacLaren Walsh
Affiliation: Electrical and Computer Engineering Department, Massachusetts General Hospital, Emory University, Drexel University
Abstract Preview: Purpose: In image-guided radiotherapy (IGRT), cone beam CTs (CBCTs) suffer from distortions that degrade registration with planning CTs. While CycleGANs can generate synthetic CTs (sCTs) from CBCTs, e...
Authors: Naruomi Akino, Kirsten Lee Boedeker, Ilmar Hein, Dylan Mather, Akira Nishikori, Daniel W Shin
Affiliation: Canon Medical Systems Corporation, Canon Medical Research USA
Abstract Preview: Purpose: To validate the performance a deep learning reconstruction (DLR) algorithm in an anatomical background compared to a uniform phantom background.
Methods: An analytic forward projection mod...
Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Christian Erik Petersen, Alex T. Price, Atefeh Rezaei, Runyon C. Woods
Affiliation: University Hospitals Seidman Cancer Center
Abstract Preview: Purpose: CBCT is subject to more artifacts due to increased photon scatter, especially in areas of increased tissue heterogeneities compared to fan-beam CTs (FBCTs). Improved imaging panels combined w...
Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Duke Kunshan University
Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...
Authors: Giavanna Luisa Jadick, Patrick J La Riviere
Affiliation: University of Chicago
Abstract Preview: Purpose: We assess two multi-measurement acquisition schemes for material decomposition with x-ray phase-contrast imaging (XPCI); demonstrating for the first time that multi-distance imaging can match...
Authors: Chih-Wei Chang, Junbo Peng, Richard L.J. Qiu, Justin Roper, Xiangyang Tang, Tonghe Wang, Huiqiao Xie, Xiaofeng Yang, David Yu
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Emory Univ, Emory University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered a promising solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, ...
Authors: Zhongjie Lu
Affiliation: Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine
Abstract Preview: Purpose: Patients with locally-advanced head and neck squamous cell carcinomas(HNSCCs), particularly those related to human papillomavirus(HPV), often achieve good locoregional control(LRC), yet they ...
Authors: Hania A. Al-Hallaq, Chih-Wei Chang, Anees H. Dhabaan, Yuan Gao, Shaoyan Pan, Junbo Peng, Richard L.J. Qiu, Keyur Shah, Sibo Tian, Zhen Tian, Xiaofeng Yang, David Yu, Jun Zhou
Affiliation: Emory University, Whinship Cancer Institute, Emory University, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Traditional cone-beam computed tomography (CBCT) often requires multiple angular projections, increasing radiation exposure and extending scanning times, which may lead to heightened patient ...
Authors: Ruiyan Du, He Huang, Mingzhu Li, Ying Li, Hongyu Lin, Wei Liu, Shihuan Qin, Yiming Ren, Hui Xu, Lian Zhang, Xiao Zhang, Zunhao Zhang
Affiliation: Department of Radiation Oncology, Mayo Clinic, Medical AI Lab, The First Hospital of Hebei Medical University, Hebei Provincial Engineering Research Center for AI-Based Cancer Treatment Decision-Making, The First Hospital of Hebei Medical University, Department of Oncology, The First Hospital of Hebei Medical University
Abstract Preview: Purpose: Monte Carlo (MC) dose calculation is the gold standard in clinical CyberKnife radiation therapy (RT), considering its steep dose gradients and high-freedom non-coplanar beam angles, but extre...
Authors: Matthew Brown, Yushi Chang, Jinhyuk Choi, William Silva Mendes, Lei Ren, Aman Sangal, William Paul Segars, Phuoc Tran, Hualiang Zhong
Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: Digital phantoms like XCAT are essential for imaging and treatment optimization in radiology and radiation oncology. However, the lack of realistic textures (HU distribution) in XCAT limits i...
Authors: Samuel Kadoury, Redha Touati
Affiliation: Polytechnique Montréal
Abstract Preview: Purpose:
Generating synthetic CT images from MR acquisitions for radiotherapy planning allows to integrate soft tissue contrast alongside density information stemming from CT, thus improving tumor ...
Authors: Yizheng Chen, Michael Gensheimer, Mingjie Li, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: Automatically translating non-contrast to contrast-enhanced computed tomography (CT) images is critical for improving clinical workflow, reducing heathcare cost, minimizing radiation exposure...
Authors: Jing Qian, Brandon Reber, David M. Routman, Satomi Shiraishi
Affiliation: Mayo Clinic
Abstract Preview: Purpose: The dose distribution in proton radiotherapy (PRT) is characterized by sharp gradients, posing a challenge for machine learning-based dose prediction. While denoising with diffusion processes...
Authors: Lu Jiang, Ke Sheng
Affiliation: Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco
Abstract Preview: Purpose:
Conventional radiotherapy treatment planning is guided by a set of generic objectives that are unspecific to patient anatomy. Treatment planning thus heavily relies on the planner’s experi...
Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang
Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, Peopleʼs Republic of China
Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...