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Results for "cine mris": 38 found

12 Year Clinical Experience with Low-Tesla MRI for Tumor Progression

Authors: Soon N. Huh, Perry B. Johnson, Jiyeon Park, Ryan Stevens

Affiliation: University of Florida Health Proton Therapy Institute, UF Health Proton Therapy Institute, UFHPTI

Abstract Preview: Purpose:
Low-Tesla MRI (0.23T Panorama MR Scanner, Philips) has been used for tumor progression during proton therapy treatments, and for initial contouring in addition to diagnostic MRI. The pulse...

4D Monte Carlo Dose Evaluation for Mobile Targets in a Magnetic Field

Authors: Odunola Grace Babawale, B. Gino Fallone, Alireza Gazor, Andrei D. Ghila, Patricia A. K. Oliver, Michael W. Reynolds, Keith D. Wachowicz, Tania Rosalia Wood, Shima Y. Tari, Eugene Yip, Jihyun Yun

Affiliation: Nova Scotia Health, Dept. of Medical Physics and Dalhousie University, Dept. of Physics and Atmospheric Science, Dept. of Radiation Oncology, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com, Department of Medical Physics, Arthur J. E. Child Comprehensive Cancer Centre, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Department of Medical Physics, BC Cancer, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute

Abstract Preview: Purpose: To evaluate the dose to a moving target and its surroundings in a magnetic field using 4D-Monte-Carlo (MC) simulation.
Methods: The study utilizes a previously validated MC model of our li...

A Deformable Registration-Based Pipeline for the Characterisation of Respiratory Motion from 2D Lung Cine MRI

Authors: Michael W. Kissick, Chung Tin Lo, Jamie R McClelland, Niek Schreuder, Tracy Underwood

Affiliation: Hawkes Institute, University College London, Leo Cancer Care

Abstract Preview: Purpose: The emerging field of upright radiotherapy raises the question of how respiratory motion differs between upright and supine treatment postures. Therefore, we have developed a versatile pipeli...

A Retrospective Assessment of Proton Radiation Response in Brain Tumor Patients Using Diffusion-Weighted MR Imaging

Authors: Liu Hong, Wen C. Hsi, Faraz Kalantari, Romy Megahed, Ganesh Narayanasamy, Maida Ranjbar, Pouya Sabouri, Zhong Su

Affiliation: University of Arkansas for Medical Sciences, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)

Abstract Preview: Purpose: Quantitative apparent diffusion coefficients (ADC) in diffusion-weighted MRI (dMRI) reflect water diffusivity and thus provide tissue cellular density information. Functional diffusion mappin...

A SAM-Guided and Match-Based Semi-Supervised Segmentation Framework for Medical Imaging

Authors: Weiguo Lu, Jax Luo, Xiaoxue Qian, 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, Harvard Medical School

Abstract Preview: Purpose:
Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. This study leverages th...

A Study of Large Model Alignment Techniques for MRI Images of Small Sample Meningioma

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...

Assessing Breast Cancer Tumor Segmentability on an Investigational, Double-Bolus, Prone-to-Supine Breast MRI Protocol for Surgical Guidance.

Authors: Richard J Barth, Brook Kennedy Byrd, Roberta DiFlorio-Alexander, Misty J Fox, Venkat Krishnaswamy, Keith D. Paulsen, Timothy B Rooney

Affiliation: Cairn Surgical Inc., Dartmouth Health, Thayer School of Engineering, Dartmouth Hitchcock Medical Center, University of Virginia Health, CairnSurgical Inc.

Abstract Preview: Purpose: Supine breast MRI enables precise surgical planning with demonstrated benefit in decreasing positive margin rates during BCS. However, acquiring supine breast MRI scans in a secondary imaging...

BEST IN PHYSICS MULTI-DISCIPLINARY: Foundation Model-Empowered Unsupervised 3D Deformable Medical Image Registration

Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, Stanford University, Duke University, Stanford University

Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Box-Prompt Zero-Shot Smart Segmentation in Radiation Oncology Using a SAM-Based Model: Smartsam

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...

Comparative Analysis of Nine Deep Learning Architectures for Variable Density Grappa 1H Magnetic Resonance Spectroscopy Imaging (MRSI) Reconstruction

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 ...

Comparison of Cine Cardiac Magnetic Resonance (CMR) Imaging Performance: 0.6 T Versus 1.5 T, Is 0.6 T Fit for Purpose?

Authors: Jacinta E. Browne, Tzu Cheng Chao, Ajit Deveraj, Ece Ercan, Tim Leiner, Alessio Perazzolo, Michal Povazan, Jouke Smink, Camilla Vita, Spencer Waddle, Dinghui Wang

Affiliation: Università Cattolica del Sacro Cuore, Philips Healthcare, Mayo Clinic

Abstract Preview: Purpose:
In recent years, mid-field MRI has shown promise to meet the technical demands of cardiac imaging1. Mid-field strengths offer advantages to CMR due to shorter T1-relaxation times, lower sp...

Comparison of Frame-Based and Frameless Gamma Knife Coordinate Spaces for Treatment of Trigeminal Neuralgia

Authors: Tatiana Bejarano, Omer Gal, Alonso N. Gutierrez, Matthew D. Hall, Rupesh Kotecha, Yongsook C. Lee, Michael W. McDermott, Minesh P. Mehta, Robert H. Press, Carlos M. Rivera, Ranjini P. Tolakanahalli, D. Jay J. Wieczorek

Affiliation: Miami Cancer Institute, Baptist Health South Florida

Abstract Preview: Purpose:
Gamma Knife (GK) cone beam computed tomography-based stereotactic reference (CBCTRef) combined with pre-planning MRI, provides a flexible alternative to the historical frame-based localiza...

Demystifying Magnetic Resonance Imaging: Targeted Educational Initiatives for Medical Physicists in Türkiye and Preclinical Medical Students in the United States

Authors: Samuel A. Einstein, Jesutofunmi Fajemisin, Evren O. Göksel, Görkem O. Güngör, Marthony Robins, Travis C. Salzillo, Charles R. Thomas, Turgay Toksay, Joseph Weygand, Yue Yan

Affiliation: Acibadem MAA University, Department of Radiation Oncology and Applied Science, Dartmouth Health, Dartmouth College, Moffitt Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Penn State College of Medicine, Bursa Ali Osman Sönmez Oncology Hospital

Abstract Preview: Purpose: Magnetic resonance imaging (MRI) is an indispensable clinical tool, offering unparalleled soft tissue contrast critical for diagnosing and managing a wide range of conditions. However, its co...

Development and Clinical Validation of Hyperarc Stereotactic Radiosurgery Method for Intraocular Tumors

Authors: Chase Cochran, Damodar Pokhrel, William St Clair

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Radiation Medicine

Abstract Preview: Purpose: Currently, intraocular disease is primarily treated via COMS-plaques brachytherapy. Various stereotactic approaches via photons/proton beam have also been implemented (CyberKnife/GammaKnife/p...

Development and Implementation of MRI-Only Simulation, Planning and Treatment Workflow for Pelvic Radiotherapy Using Synthetic CT on MR-Linac

Authors: Peter Balter, Elaine Eunnae Cha, Seungtaek Choi, Yao Ding, Eun Young Han, Yusung Kim, Rajat J. Kudchadker, Belinda Lee, Surendra Prajapati, Reza Reiazi, Ergys D. Subashi, Sarath Vijayan, Jinzhong Yang, Yao Zhao

Affiliation: The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: This study evaluates the feasibility of an MR-only simulation, planning, and treatment (MROSPT) workflow for pelvic cancer patients using synthetic CT generated from MRI data. By validating s...

Development of an MRI Guided Precision Small Animal Radiotherapy System

Authors: Yaowen Cao, Yunwen Huang, Yidong Yang, Xiaogang Yuan, Ning Zhao, Cheng Zheng

Affiliation: Department of Life Sciences and Medicine, University of Science and Technology of China, Department of Engineering and Applied Physics, University of Science and Technology of China, University of Science and Technology of China

Abstract Preview: Purpose: MRI has better soft tissue contrast than cone beam CT which is commonly used in image guided radiotherapy. This study aims to develop a low-field MRI system for precision small animal radiati...

Dosimetric Evaluation of Clinical Venezia Hybrid Applicator Plans Using a TG-186 Model-Based Dose Calculation Algorithm

Authors: Davide Brivio, Ivan M. Buzurovic, Thomas C. Harris, Desmond A. O'Farrell

Affiliation: Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology

Abstract Preview: Purpose: Cervical cancer can be treated with a brachytherapy boost following external beam radiotherapy. One applicator option is the Advanced Gynecological Applicator "Venezia" (Elekta) hybrid, consi...

Enhancing Radiation Oncology Imaging with a Novel Variational Model Decomposition, Radon Transformation, and Kohonen Self-Organizing Map Denoising Framework

Authors: Hassan Bagher-Ebadian, Justine M. Cunningham, Anthony J. Doemer, Mohammad M. Ghassemi, Joshua P. Kim, Benjamin Movsas, Kundan S Thind

Affiliation: Michigan State University, Henry Ford Health

Abstract Preview: Purpose: Reduction of noise in medical images critically enables improved accuracy in delineating tumors and organs at risk, leading to more precise treatment planning and safer image-guided radiation...

Fine-Tuning AI-Based Generative Models for Small-Sample Glioma MRI Generation.

Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, 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, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...

Generalized 2D Cine Multi-Modal MRI-Based Dynamic Volumetric Reconstruction Using Motion-Aligned Implicit Neural Network with Spatial Prior Embedding

Authors: Ming Chao, Karyn A Goodman, Yang Lei, Tian Liu, Jing Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose: Real-time volumetric MRI is essential for motion management in MRI-guided radiotherapy (MRIgRT), yet acquiring high-quality 3D images remains challenging due to time constraints and motion ar...

Geometrically Derived Density Compensation Function for 3D Non-Cartesian MRI Reconstruction

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...

Improving 4D-MRI Parameters for Abdominal Tumor Motion Management: A Phantom Study

Authors: Morgan Aire, Krystal M. Kirby, Olivia Magneson, David E. Solis

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: For soft-tissue abdominal tumors, a 4D-MR may provide improved tumor tracking over the clinical standard 4D-CT. This project aims to optimize a clinically available 4D-MR pulse sequence to ac...

Improving the Robustness of AI-Based Detection and Segmentation for Brain Metastasis By Optimizing Loss Function and Multi-Dataset Training

Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte

Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine

Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...

Integrated Catheter Position and Dwell Time Optimization for Focal Dose Escalation in Prostate HDR Brachytherapy

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...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

Affiliation: University of Illinois at Urbana Champaign, University of Illinois at Urbana-Champaign, Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

Inter-Fraction Monitoring of Brain Metastases Resection Cavities during Fractionated Stereotactic Radiosurgery on the 0.35 T MRI-Linac

Authors: Eyub Y. Akdemir, Gregory A Azzam, Rupesh Kotecha, Gregory J. Kubicek, Natalia Lutsik, Eric Mellon, Siamak P. Nejad-Davarani, Parag Parikh, Karen C. Snyder

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Department of Radiation Oncology, University of Miami, Henry Ford Health

Abstract Preview: Purpose: Resection cavity volumes shrink gradually over time after surgical resection of brain metastases. Fractionated stereotactic radiosurgery (fSRS) is often delivered to the cavity to prevent rec...

Motion Correction-Driven Patient-Specific 2D Cine MRI-Based Dynamic Volumetric Reconstruction for MRI-Guided Radiotherapy Intra-Fractional Motion Monitoring

Authors: Karyn A Goodman, Yang Lei, Tian Liu, D. Michael Lovelock, Charlotte Elizabeth Read, Jing Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose: Real-time volumetric MRI is essential for precise motion management in MRI-guided radiotherapy (MRIgRT). While 2D Cine MRI offers high temporal resolution for motion tracking, it inherently l...

Optimized Dosimetric Planning for Trigeminal Neuralgia Using Cyberknife S7 Precision TPS with Volo Optimizer

Authors: Amy Fitzpatrick, Kim Howard, Julius G. Ojwang, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: This study evaluates the dosimetric advantages and workflow improvements of the CyberKnife S7 Precision Treatment Planning System (TPS) with the VOLO optimizer for stereotactic radiosurgery (...

Patient-Specific Ultra-Sparse k-Space Reconstruction Using Motion Decomposition and Sinusoidal Representation Networks for Dynamic Volumetric MRI in Radiotherapy

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Charlotte Elizabeth Read, Jing Wang, Qian Wang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Beth Israel Deaconess Medical Center

Abstract Preview: Purpose: Accurate motion management in MRI-guided radiotherapy (MRIgRT) relies on real-time volumetric MRI to track intra-fractional anatomical changes. Dense k-space sampling, while capable of produc...

Radiation Sub-Segmentectomy in 90y Radioembolization: Post-Therapy Dosimetry, Treatment Response, and Pathological Necrosis

Authors: Guilherme Rosa Ferreira, Dan Giardina, John Karageorgiou, Chris Malone, Allan Thomas

Affiliation: Washington University School of Medicine, Mallinckrodt Institute of Radiology, Washington University School of Medicine

Abstract Preview: Purpose: Radiation segmentectomy has become a primary strategy in 90Y radioembolization, with localized treated volumes that can include up to two liver segments. The goal is complete pathological nec...

Robust Estimation of Cell Microstructure Parameters Via Diffusion MRI Cytometry

Authors: Yan Dai, Jie Deng, Xun Jia, Wen Li

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University, Medical Artificial Intelligence and Automation (MAIA) Laboratory, 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: Cell microstructure information is critical for radiotherapy response assessment. Diffusion MRI (dMRI) offers great potential in deriving cell parameters. Yet parameters estimated in existing...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

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 ...

Sources of Magnetic Susceptibility Artifacts in MR Imaging of the Jaw and Facial Nerves

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...

Synthetic CT Generation from a Cycle Diffusion Model Based Framework for Ultrasound-Based Prostate HDR Brachytherapy

Authors: Michael Baine, Charles Enke, Yang Lei, Yu Lei, Ruirui Liu, Su-Min Zhou

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Radiation Oncology, University of Nebraska Medical Center

Abstract Preview: Purpose: This study presents a framework for generating synthetic CT images using a Cycle Diffusion model, which can be utilized to enhance needle conspicuity in ultrasound-guided prostate HDR brachyt...

Towards Penile Small Vessel Imaging with Ferumoxytol-Enhanced MRI

Authors: Darren Fang, Amar Kishan, Justin McWilliams, Dan Ruan, Xiaodong Zhong

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of California, Los Angeles, Department of Radiological Sciences, University of California, Los Angeles

Abstract Preview: Purpose: Prostate radiotherapy can malform penile vasculature, contributing to erectile dysfunction and compromising quality of life. To detect, quantify, and preferably avoid such occurrences, this p...

Universal Anatomical Mapping and Patient-Specific Prior Implicit Neural Representation for MRI Super-Resolution

Authors: Jie Deng, Yunxiang Li, 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: Magnetic Resonance Imaging (MRI) has exceptional soft tissue contrast and an essential role in radiotherapy. The introduction of clinical MR-LINACs has enabled adaptive radiotherapy (ART) usi...

Using Multiple Sequences MRI for Synthesizing CT Based on a Deep Learning Approach

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...