Authors: Ziheng Deng, Yao Hao, Runping Hou, Deshan Yang, Jun Zhao, Yufu Zhou
Affiliation: Department of Radiation Oncology, Duke University, School of Biomedical Engineering, Shanghai Jiao Tong University, Washington University School of Medicine, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: 4D CBCT has been developed to provide dynamic images for image-guided radiation therapy. However, as projection data are sorted into sparse and clustered phase-specific bins, 4D CBCT images a...
Authors: Yunxiang Li, Hua-Chieh Shao, Chenyang Shen, Jing Wang, Jiacheng Xie, Shunyu Yan, 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, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas
Abstract Preview: Purpose: Accurate liver deformable motion tracking is essential in image-guided radiotherapy to enable precise tumor targeting during treatment. We developed a conditional point cloud diffusion model ...
Authors: Suman Gautam, Tianjun Ma, William Song
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: We propose an artificial intelligence (AI)-based method to rapidly predict the patient-specific quality assurance (PSQA) results for magnetic resonance (MR)-guided online adaptive radiation th...
Authors: Xiaoxue Qian, Hua-Chieh Shao, 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:
Limited-angle CBCT (LA-CBCT) reduces imaging time and dose but suffers from under-sampling artifacts. 2D–3D deformable registration addresses this problem by estimating LA-CBCTs from defor...
Authors: Wenfeng He, Tian Liu, Pretesh Patel, Richard L.J. Qiu, Keyur Shah, Tonghe Wang, Xiaofeng Yang, Chulong Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Emory University, Medical Physics Graduate Program, Duke Kunshan University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study introduces a tracking-free approach to reconstruct 3D ultrasound (US) volumes from 2D freehand US scans. By eliminating the reliance on external tracking systems, this method aims ...
Authors: Eric Chang, Nguyen Phuong Dang, Andrew Lim, Lauren Lukas, Lijun Ma, Yutaka Natsuaki, Zhengzheng Xu, Hualin Zhang
Affiliation: Radiation Oncology, Keck School of Medicine of USC
Abstract Preview: Purpose: Harnessed the power of AI and Deep Learning (DL), Generalized Neural Network models for medical image transformation are trained to predict target images from reference images, often requirin...
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: 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: Rani Anne', Wenchao Cao, Yingxuan Chen, Wookjin Choi, Firas Mourtada, Yevgeniy Vinogradskiy
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: In-room mobile cone-beam CT (CBCT) is emerging to enhance high-dose-rate (HDR) brachytherapy workflow using on-demand imaging. However, metal artifacts from X-ray markers inside gynecological...
Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jing Sun, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Xiaojing Zhu
Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Shanghai University of Electric Power, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Accurate prediction of patient response to radiotherapy plays a crucial role in monitoring disease progression and assessing treatment efficacy, enabling clinicians to develop personalized th...
Authors: Giovanni Iacca, Gloria Miori, Laura Orsingher, Daniele Ravanelli, Annalisa Trianni
Affiliation: Department of Information Engineering and Computer Science, University of Trento, Medical Physics Department, S.Chiara Hospital, APSS
Abstract Preview: Purpose: This study aims to leverage artificial intelligence (AI) to predict and identify performance degradation in Digital Radiography (DR) systems, enabling proactive maintenance and minimizing cli...
Authors: Adayabalam Balajee, Elijah Berberette, Maria Escalona, Dray Gentry, Chester R. Ramsey, Terri Ryan
Affiliation: ORAU, Thompson Proton Center, University of Tennessee
Abstract Preview: Purpose:
Dicentric chromosomes, characterized by two centromeres on a single chromosome, are key biomarkers in biological dosimetry for quantifying ionizing radiation exposure. However, manual dete...
Authors: Xiaolong Fu, Runping Hou, Md Tauhidul Islam, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: To introduce a novel schematic image representation of radiomics data, called OmicsMap, for high-performance deep radiomics analysis. OmicsMap transforms tabular radiomics data into an image ...
Authors: Beth Bradshaw Ghavidel, Benyamin Khajetash, Yang Lei, Meysam Tavakoli
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Emory University, Department of Radiation Oncology, Emory University
Abstract Preview: Purpose: Pancreatic cancer is among the most aggressive types of cancer, with a five-year survival rate of approximately 10%. Recent studies show that radiomics and deep learning (DL)-based methods ar...
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: Lei Xing, Zixia Zhou
Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University, Stanford
Abstract Preview: Purpose: Functional brain imaging techniques, such as functional magnetic resonance imaging (fMRI), generate high-dimensional, dynamic data reflecting complex neural processes. However, extracting rob...
Authors: Yabo Fu, Yang Lei, Yu Lei, Haibo Lin, Ruirui Liu, Tian Liu, Kenneth Rosenzweig, Charles B. Simone, Shouyi Wei, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York Proton Center
Abstract Preview: Purpose: Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is traditionally a complex, non-convex problem tackled with heuristic methods. This study benchmarks global...
Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University
Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...
Authors: Liyuan Chen, Steve Jiang, Chenyang Shen
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Delays in radiation therapy (RT) initiation caused by conventional CT simulation processes can hinder timely treatment delivery and patient outcomes. This study proposes a Virtual Treatment S...
Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University
Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...
Authors: Sam Beddar, Jason Michael Holmes, Daniel G. Robertson, James J. Sohn, Ethan D. Stolen
Affiliation: Department of Radiation Oncology, Mayo Clinic, MD Anderson Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago
Abstract Preview: Purpose: Camera-based scintillation dosimetry incorporating large volumes have shown promise for fast and comprehensive evaluation of external beam treatment fields. While some efforts have been made ...
Authors: Ashok Bhandari, Kurtis Johnson, Yu Lei, Tianzhe Li, Kyuhak Oh, Shuo Wang, Chi Zhang, Su-Min Zhou
Affiliation: University of Nebraska Medical Center
Abstract Preview: Purpose: The purpose of this study was to leverage neural network visualization tools to detect high-attention areas indicative of treatment failure in lung SBRT by examining correlation matrices betw...
Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki, Bohua Wan
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Department of Computer Science, Johns Hopkins University
Abstract Preview: Purpose: Cerebellar mutism syndrome (CMS) is the most frequently observed complication in children undergoing surgical resection of posterior fossa tumors. Previous work explored lesion to symptom map...
Authors: Serdar Charyyev, Cynthia Fu-Yu Chuang, Veng Jean Heng, Lianli Liu, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: To replace large finite-size photon phase space files with a compact neural network capable of generating an infinite number of particles.
Methods: Three separate models were developed to ...
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 ...
Authors: Ji Hye Han, Yookyung Kim, Jang-Hoon Oh, Heesoon Sheen, Han-Back Shin
Affiliation: Ewha Womans university, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, High-Energy Physics Center, Chung-Ang Universit, Ewha Womans University, Kyung Hee University Hospital
Abstract Preview: Purpose: Chest X-rays are critical for diagnosing conditions such as pneumonia, tuberculosis, and COVID-19. Although deep learning (DL) approaches, especially convolutional neural networks, have signi...
Authors: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price
Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering
Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...
Authors: Fangfen Dong, Jiaming Li, Xiaobo Li, Weipei Wang, Zhixin Wang, Bing Wu, Benhua Xu, Yong Yang, Yifa Zhao
Affiliation: Department of Radiation Oncology, Fujian Medical University Union Hospital/Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors/Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematologi, Zhangpu County Hospital, School of Medical Imaging, Fujian Medical University
Abstract Preview: Purpose: To explore the construction and clinical application value of a deep learning-based positioning error prediction model, providing a reference for optimizing iSCOUT system-guided precision rad...
Authors: Zhaoyang Fan, Eric Nguyen, Dan Ruan, Jiayu Xiao
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of Southern California, University of Southern California
Abstract Preview: Purpose: MR vessel wall imaging (VWI) has been shown to be effective for evaluating intracranial atherosclerosis disease. However, VWI typically also requires an MR angiography (MRA) in the same imagi...
Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang
Affiliation: Duke University Medical Center
Abstract Preview: Purpose: Convergence speed is crucial for an optimizer. Faster convergence leads to better solutions with fewer iterations and less time. Recently, a machine learning (ML)-assisted framework employing...
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: William F.B Igoniye, Belema Manuel, Christopher F. Njeh, O Ray-offor
Affiliation: Indiana University School of Medicine, Department of Radiation Oncology, Department of Radiology, University of Port Harcourt Teaching Hospital
Abstract Preview: Purpose: The accurate and efficient categorization of brain tumors is essential for effective treatment planning and improved patient outcomes. Current MRI-based diagnostic methods are time-intensive ...
Authors: Sang Hee Ahn, Nalee Kim, Do Hoon Lim
Affiliation: Samsung Medical Center, Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine
Abstract Preview: Purpose: MRI offers superior soft-tissue contrast, aiding tumor localization and segmentation in radiation therapy, which traditionally relies on oncologists' expertise. This study compares CNN-based ...
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: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity
Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...
Authors: Lucy Jiang, Chengyu Shi
Affiliation: Department of Radiation Oncology, City of Hope Orange County, Amity Regional High School (10th Grade)
Abstract Preview: Purpose: Early-stage breast cancer is common among females, with typically high local tumor control rates (LCR). Brachytherapy is a common way to achieve LCR following surgery. However, the patients m...
Authors: Daniel H. Bushe, Arthur Lalonde, Hoyeon Lee, Harald Paganetti, Brian Winey
Affiliation: Universite de Montreal, Massachusetts General Hospital, Massachusetts General Hospital and Harvard Medical School, University of Hong Kong
Abstract Preview: Purpose: Improving the precision and fidelity of daily volumetric imaging is essential for enabling adaptive proton therapy (APT). While cone-beam CT (CBCT) provides daily volumetric imaging, their ut...
Authors: Sean L. Berry, Weixing Cai, Laura I. Cervino, Yabo Fu, Daphna Gelblum, Wendy B. Harris, Xiuxiu He, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Boris Mueller, Huiqiao Xie, Mitchell Yu, Hao Zhang
Affiliation: Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Gating ablative radiotherapy for pancreatic cancer accounts for tumor movement due to respiration and typically requires 5, 15, or 25 fractions. Pretreatment imaging verification is essential...
Authors: Amar Kishan, Jun Lian, Yunkui Pang, Jonathan Pham, X. Sharon Qi, Michael Steinberg, Luca F Valle, Pew-Thian Yap
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of North Carolina at Chapel Hill
Abstract Preview: Purpose: Stereotactic body radiotherapy (SBRT) is a highly effective treatment for prostate cancer, yet predicting genitourinary (GU) toxicity has primarily relied on planned dosimetry. This study inv...
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: Yang Lei, Tian Liu, Ren-Dih Sheu, Meysam Tavakoli, Jing Wang, Kaida Yang, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Emory University
Abstract Preview: Purpose:
The study aimed to improve target and organ at risk (OAR) segmentation in low-dose-rate brachytherapy (LDR-BT) for prostate cancer treatment, by integrating clinical guidelines into deep l...
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: Jacob S. Buatti, Kristen A. Duke, Malena Fassnacht, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia, Michelle de Oliveira
Affiliation: The University of Texas San Antonio, UT Southwestern Medical Center, UT Health San Antonio
Abstract Preview: Purpose:
Quantifying and visualizing uncertainty is critical for building clinical trust in AI-generated dose distributions. This study evaluates Monte Carlo Dropout (MCD), Snapshot Ensemble (SE), ...
Authors: Hania A. Al-Hallaq, Xuxin Chen, Anees H. Dhabaan, Elahheh (Ella) Salari, Xiaofeng Yang
Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose:
Radiomics image analysis could lead to the development of predictive signatures and personalized radiotherapy treatments. However, variations in delineation are known to affect hand-crafte...
Authors: Shinichiro Mori, Isabella Pfeiffer, Chester R. Ramsey, Alexander Usynin
Affiliation: Thompson Proton Center, National Institutes for Quantum Science and Technology, Thompson Cancer Survival Center
Abstract Preview: Purpose: Four-dimensional CT imaging (4DCT) has become a standard tool for managing respiratory motion in radiation therapy. However, many treatment delivery systems and most diagnostic CT scanners la...
Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Xiuxiu He, Tianfang Li, Xiang Li, Hao Zhang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose:
This work aims to develop an innovative technique to evaluate patients’ daily respiratory pattern using three-dimensional (3D) deformation vector fields (DVF) derived from a free-breathing...
Authors: Adnan Jafar, Xun Jia, Michael B. Roumeliotis
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University
Abstract Preview: Purpose: HDR brachytherapy (HDRBT) treatment planning is challenging due to the need for high-quality plans under time pressure, considering anatomy and applicator geometry. This study proposes an exp...
Authors: Louis Archambault, Nicolas Drouin, Alexis Horik, Simon Thibault
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, et Centre d'optique, photonique et laser, Université Laval
Abstract Preview: Purpose: To develop a novel type of real-time 3D dosimeter for the quality assurance of linear accelerators used in external beam radiotherapy.
Methods: An experimental setup was constructed using ...
Authors: Lindsay Hammons, Lisa Baumann Kreuziger, Haidy G. Nasief, Matthew Scheidt, Farrell Sean, Antonio Sosa Lozano
Affiliation: Division of Hematology and Oncology, University of Washington, Vascular and Interventional Radiology, Medical college of wisconsin, Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: Venous thromboembolism, which includes pulmonary embolism (PE), is the third leading cause of acute cardiovascular syndrome behind myocardial infarction and stroke. Current research categoriz...
Authors: Sofia Beer, Menal Bhandari, Alec Block, Nader Darwish, Joseph Dingillo, Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Rajkumar Kettimuthu, Jason Patrick Luce, Ha Nguyen, John C. Roeske, George K. Thiruvathukal, Austin Yunker
Affiliation: Data Science and Learning Division, Argonne National Laboratory, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago, Department of Computer Science, Loyola University of Chicago
Abstract Preview: Purpose: Artificial intelligence (AI) generated synthetic medical images are seeing increased use in radiology and radiation oncology. Physician observer studies are an ideal way to evaluate the usabi...
Authors: Prabhu C. Acharya, Hassan Bagher-Ebadian, Stephen L. Brown, James R. Ewing, Mohammad M. Ghassemi, Benjamin Movsas, Farzan Siddiqui, Kundan S Thind
Affiliation: Michigan State University, Oakland University, Henry Ford Health
Abstract Preview: Purpose: Accurate T1 quantification using T One by Multiple Read Out Pulse (TOMROP) sequences is essential for physiological assessments in dynamic-contrast-enhanced (DCE) MRI and T1 mapping studies. ...
Authors: Yasin Abdulkadir, John Charters, Melissa Ghafarian, James M. Lamb, Dishane Chand Luximon, Jack Neylon
Affiliation: Department of Radiation Oncology, University of California, Los Angeles
Abstract Preview: Purpose:
Assessment of radiotherapy treatment quality in large-scale multi-institutional contexts remains an outstanding challenge. Retrospective human review of treatment plans is labor intensive ...
Authors: Yoonha Eo
Affiliation: Yonsei University
Abstract Preview: Purpose: To develop a fully automatic and unsupervised algorithm for estimating the Exposure Index (EI) of various Regions of Interest in X-ray imaging using advanced foundation models. Traditional EI...
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...
Authors: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh
Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences, Tehran University of Medical Science
Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...
Authors: Pouya Azarbar, Nima Kasraie, Peyman Sheikhzadeh
Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences
Abstract Preview: Purpose: Positron Emission Tomography (PET) is crucial for diagnosing and monitoring diseases due to its functional imaging capabilities. However, its high cost, significant radiation exposure, and li...
Authors: Ross I. Berbeco, Vera Birrer, Raphael Bruegger, Pablo Corral Arroyo, Roshanak Etemadpour, Dianne M. Ferguson, Rony Fueglistaller, Thomas C. Harris, Yue-Houng Hu, Matthew W. Jacobson, Mathias Lehmann, Nicholas Lowther, Daniel Morf, Marios Myronakis
Affiliation: Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology, Dana Farber/Brigham and Women's Cancer Center, Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Womens Hospital, Dana Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Varian Imaging Laboratory, Dana-Farber Cancer Institute
Abstract Preview: Purpose: Applications of combined kV-MV CBCT include metal artifact correction and material identification. Difficulties arise, however, when the imagers have misaligned geometric perspectives of the ...
Authors: Enhui Chang, Yunfei Dong, Yifei Hao, Chengliang Jin, Shengsheng Lai, Yi Long, Mengni Wu, Yulu Wu, Ruimeng Yang, Zhenyu Yang, Yue Yuan, Lei Zhang, Wanli Zhang, Yaogong Zhang
Affiliation: Duke Kunshan University, Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Macrotrabecular-Massive Hepatocellular Carcinoma (MTM-HCC) is one type of liver cancer showed minimum image signature for accurate non-invasive diagnosis. This study aims to develop and evalu...
Authors: Wilfred R Furtado, Gary Y. Ge, James Lee, Jie Zhang
Affiliation: University of Kentucky
Abstract Preview: Purpose: Despite advancements in Artificial Intelligence (AI) and its growing role in clinical practices like radiology, formal AI education remains limited in medical training. This gap contributes t...
Authors: Yu Gao, Lei Xing, Siqi Ye
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose:
Limited-angle CBCT (LA-CBCT) scans are often the only option for non-coplanar radiation therapy to prevent potential mechanical collisions. However, the consecutive angular occlusion of pr...
Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Huiqiao Xie, Hao Zhang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: This study introduces a novel spatiotemporal Gaussian neural representation framework to reconstruct high-temporal dynamic CBCT images from 1-minute acquisition, preserving motion dynamics an...
Authors: Renee Farrell, Jinkoo Kim, Xin Qian, Ziyu Shu, Zhaozheng Yin, Tiezhi Zhang
Affiliation: Stony Brook Medicine, Washington University in St. Louis, Stony Brook University, Stony Brook University Hospital
Abstract Preview: Purpose: Ultra-short CT scan allows fast imaging speed, dose reduction, and compact system design. We developed a deep image prior (DIP) based reconstruction method named Hybrid Prior-Enhanced Deep Im...
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: John Ginn, Chenlu Qin, Deshan Yang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: Clinical implementation of auto-segmentation tools has been hindered by poor interpretability and generalizability of AI models, necessitating the development of automated contour quality ass...
Authors: Marissa Brown, Geoffrey D. Clarke, Luke Norton
Affiliation: University of Texas Health Science Center at San Antonio
Abstract Preview: Purpose: To evaluate how different learning strategies affect convolutional neural network (CNN) estimates of the liver's intravoxel incoherent motion (IVIM) parameters.
Methods: A 3-stage U-Net wa...
Authors: Ara Alexandrian, Sadiki Daniel
Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center
Abstract Preview: Purpose: To develop a learning-to-optimize machine learning model that accelerates optimization in VMAT treatment planning by training on prostate patient data.
Methods: A treatment plan dataset of...
Authors: Ibtisam Almajnooni, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: We developed a deep learning neural network (DLNN) to predict the risk of radiation-induced esophagitis (RE) during lung cancer radiation therapy based on the spatial dose distribution, for t...
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: Seungryong Cho, Donghyeok Choi, Joonil Hwang, Byung-Hee Kang, Jin Sung Kim, Eungman Lee, Younghee Park
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, KAIST, Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Ewha Womans University of Medicine
Abstract Preview: Purpose: Radiation therapy (RT) is critical for cancer treatment, but changes in tumor size and shape during therapy challenge precise dose delivery. Adaptive radiation therapy (ART) addresses these v...
Authors: Ryan Alden, Tithi Biswas, Kaushik Halder, Felix Maria-Joseph, Michael Mix, Rihan Podder, Tarun Kanti Podder
Affiliation: SUNY Upstate Medical University, IIT-Roorkee, University of Florida
Abstract Preview: Purpose: Early-stage NSCLC patients undergoing SBRT often die due to intercurrent illnesses. However, prediction of overall survival (OS) remains crucial due to the risk of disease recurrence. This st...
Authors: Ali Ajdari, Thomas R. Bortfeld, Christopher Bridge, Gregory Buti, Marcela Giovenco, Fredrik Lofman, Gregory C. Sharp, Helen A Shih, Tugba Yilmaz
Affiliation: Massachusetts General Hospital, RaySearch Laboratories, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Massachusetts General Hospital and Harvard Medical School
Abstract Preview: Purpose: Defining radiation target volumes with accurate integration of the neuroanatomy is one of the major difficulties in designing glioma treatments. We developed a deep learning network for norma...
Authors: Akihiro Haga, Ren Iwasaki, Kenya Kusunose, Makoto Miyake, Kenji Moriuchi, Yasuharu Takeda, Hidekazu Tanaka, Hirotsugu Yamada
Affiliation: Department of Cardiovascular Medicine, Nephrology, and Neurology Graduate School of Medicine, University of the Ryukyus, Graduate School of Biomedical Sciences, Tokushima University, Tokushima university, Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Department of Cardiology, Tenri Hospital, Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Division of Heart Failure, Department of Heart Failure and Transplant, National Cerebral and Cardiovascular Center
Abstract Preview: Purpose: Device dependency is a significant challenge in medical AI, potentially limiting generalization performance. This study aimed to develop a robust deep learning model for predicting left ventr...
Authors: Yufeng Cao, Luigi Marchionni, William Silva Mendes, Cem Onal, Lei Ren, Amit Sawant, Nicole L Simone, Philip Sutera, Phuoc Tran
Affiliation: University of Maryland School of Medicine, 9Department of Radiation Oncology, Thomas Jefferson University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, University of Maryland, Baltimore, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine, Maryland University Baltimore, 8Department of Pathology and Laboratory Medicine, Weill Cornell Medicine
Abstract Preview: Purpose: This study aims to predict 2-yr Metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) patients treated by metastasis-directed therapy (MDT) by devel...
Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi
Affiliation: UC San Diego, Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...
Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao
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, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...
Authors: Liyuan Chen, Meixu Chen, Bowen Jing, Sepeadeh Radpour, Erich Josef Schmitz, David Sher, Jing Wang
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: Prospective clinical trials have shown that involved nodal radiation therapy (INRT) can substantially improve patients’ quality of life without increasing the risk of elective nodal failure. ...
Authors: Ali Ajdari, Alice Bondi, Thomas R. Bortfeld, Gregory Buti, Xinru Chen, Zhongxing Liao, Antony John Lomax, Ting Xu
Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Paul Scherrer Institut, ETH Zurich
Abstract Preview: Title: Addressing Imaging and Biomarker-driven Uncertainty in Machine Learning-based Radiotherapy Outcome Prediction
Alice Bondi, Gregory Buti, Antony Lomax, Thomas Bortfeld, Xinru Chen, Ting Xu, Z...
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: Yunfei Dong, Dongyang Guo, Jiongli Pan, Tao Peng, Caiyin Tang, Zhenyu Yang, Fang-Fang Yin, Lei Zhang, Tianyi Zhang, Yaogong Zhang
Affiliation: Duke Kunshan University, Department of Radiology, Taizhou People’s Hospital Affiliated to Nanjing Medical University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to improve the accuracy of CT-based diagnosis of thyroid cancer by developing a hybrid model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...
Authors: Steve B. Jiang, Mu-Han Lin, Yu-Chen Lin, Austen Matthew Maniscalco, Dan Nguyen, David Sher, Xinran Zhong
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, UT Dallas
Abstract Preview: Purpose:
Sequential boost radiotherapy (RT) poses a challenge in allocating dose across multiple plans while protecting organs at risk (OARs). Clinicians must decide whether OAR sparing should occu...
Authors: Martin Frank, Oliver Jäkel, Niklas Wahl
Affiliation: Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Karlsruhe Institute of Technology (KIT)
Abstract Preview: Purpose: Machine learning (ML) models on normal tissue complication and tumor control probability ((N)TCP) exploiting e.g. dosiomic and radiomic features are playing an increasingly important role in ...
Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu
Affiliation: Wayne State University, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health
Abstract Preview: Purpose: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...
Authors: Daniel O Connor, Mary Feng, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger, Jess E. Scholey, Ke Sheng, DI Xu, Wensha Yang, Yang Yang
Affiliation: UCSF, University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, University of San Francisco, Department of Radiology, University of California, San Francisco, University of California San Francisco, Siemens Medical Solutions USA Inc.
Abstract Preview: Purpose: The scanning time for a fully sampled MRI is lengthy. Compressed sensing (CS) has been developed to minimize image artifacts in accelerated scans, but the required iterative reconstruction is...
Authors: Peng Dong, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University, Stanford University
Abstract Preview: Purpose: Volumetric Modulated Arc Therapy (VMAT) optimization is a complex, non-convex problem with numerous variables and intricate constraints. Traditional optimization methods often lack efficiency...
Authors: Mavlonbek Khomidov, Jong-Ha Lee
Affiliation: Department of Biomedical Engineering, Keimyung University, Department of Computer Engineering, Keimyung University
Abstract Preview: Purpose: In this research, we aim to estimate blood pressure using remote photoplethysmography (rPPG) signal extracted from facial video. This method provides non-invasive and contactless, continuous ...
Authors: Yan Dai, Jie Deng, Xun Jia, Wen Li, Junzhong Xu
Affiliation: Johns Hopkins University, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiology, Vanderbilt University Medical Center, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose: Cell size is a vital parameter in evaluating the tumor microenvironment, including cell apoptosis and radiotherapy(RT)-induced immune cell infiltration. The IMPULSED(Imaging Microstructural P...
Authors: Seungtaek Choi, Laurence Edward Court, Eun Young Han, Yusung Kim, Hunter S. Mehrens, Tucker J. Netherton, Shiqin Su
Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Automated treatment planning is gaining traction for its enhanced consistency and efficiency. A key challenge, however, lies in the inability of neural network dose predictions directly trans...
Authors: Wookjin Choi, Michael Dichmann, Adam Dicker, Nilanjan Haldar, Yingcui Jia, Nicole L Simone, Eugene Storozynsky, Yevgeniy Vinogradskiy, Maria Werner-Wasik
Affiliation: Thomas Jefferson University, 9Department of Radiation Oncology, Thomas Jefferson University
Abstract Preview: Purpose: Cardiotoxicity remains a significant limitation for lung cancer patients treated with radiotherapy. Pre-radiotherapy cardiac conditions increase the probability of patients developing cardiot...
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: Hao Chen, Kai Ding, Xiaoyu Hu, Xun Jia, Heng Li, Devin Miles
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University
Abstract Preview: Purpose: Accurately delivering radiation dose is critical in intensity-modulated proton therapy (IMPT), where intrafraction motion management plays a pivotal role. Our proton therapy system equipped x...
Authors: Ricardo Garcia Santiago, Narges Miri, Daryl P. Nazareth, Ankit Pant, Mukund Seshadri
Affiliation: Roswell Park Comprehensive Cancer Center
Abstract Preview: Purpose: To develop a transformer-based deep learning network framework for predicting VMAT dose distributions. This can provide fast and efficient calculations with accuracies potentially comparable ...
Authors: Kristina Bjegovic, Yong Chen, Gilberto Gonzalez, Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu
Affiliation: University of Maryland School of Medicine, University of California, Irvine, University of Oklahoma Health Sciences Center, University of Oklahoma Health Science Center
Abstract Preview: Purpose: Proton therapy is becoming an increasingly popular choice for cancer treatment due to its precision, reduced side effects, and effectiveness. While dosimetry is fundamental to the success of ...
Authors: Osama R. Mawlawi, Yiran Sun
Affiliation: RICE University, UT MD Anderson Cancer Center
Abstract Preview: Purpose: Conventional PET reconstruction methods often produce noisy images with artifacts due to data/model mismatches and inconsistencies. Recently, deep learning-based conditional denoising diffusi...
Authors: Brian M. Anderson, Shiva K. Das, Meagan Foster, Anirudh Karunaker, Lawrence B. Marks, Lukasz Mazur, Michael Repka
Affiliation: UNC Chapel HIll, University of North Carolina at Chapel Hill, UNC School of Medicine, University of North Carolina
Abstract Preview: Purpose: Development of a peer review segmentation check system to identify deviations in physician contours of standard risk pelvic lymph nodes in patients receiving radiation therapy for prostate an...
Authors: Abdullah Hidayat, Wazir Muhammad
Affiliation: Florida Atlantic University
Abstract Preview: Purpose: This study aims to predict Head and Neck cancer using an artificial neural network (ANN) through readily available basic health data. The goal is to uncover hidden patterns and predictors in ...
Authors: Muhammad Ramish Ashraf, Clinton Gibson, Gregory Szalkowski, Lei Wang, Siqi Wang, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University School of Medicine, Stanford University
Abstract Preview: Purpose: To develop a neural network-based super-resolution framework for enhancing the resolution of sparse dosimetry measurements in patient-specific radiotherapy QA. Sparse detector arrays, such as...
Authors: Aditya P. Apte, Joseph O. Deasy, Sharif Elguindi, Aditi Iyer, Jue Jiang, Eve Marie LoCastro, Jung Hun Oh, Amita Shukla-Dave, Harini Veeraraghavan
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: We present port of popular Computational Environment for Radiological Research software platform to Python programming language to cater to cloud-based analyses.
Methods: The components of...
Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang
Affiliation: Duke University Medical Center
Abstract Preview: Purpose: Gradient-based optimization is the standard approach for IMRT fluence map optimization (FMO). Recently, a machine learning (ML)-assisted framework using a one-layer neural network was propose...
Authors: Steve B. Jiang, Austen Matthew Maniscalco, Dan Nguyen, Chenyang Shen, Jiacheng Xie, Shunyu Yan, Ying 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) Lab & Department of Radiation Oncology, UT 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: Although treatment planning systems (TPSs) can handle dose calculation and plan optimization automatically, planning for radiotherapy still requires extensive efforts and expertise from a mul...
Authors: Yankui Chang, Shijun Li, Xi Pei, Ripeng Wang, Xuanhe Wang, X. George Xu, Qing Zhang, Jingfang Zhao
Affiliation: University of Science and Technology of China, Shanghai proton and heavy ion center, School of Nuclear Science and Technology, University of Science and Technology of China, Anhui Wisdom Technology Co., Ltd.
Abstract Preview: Purpose:
This paper describes disruptive methods using both GPU-based MC simulation and deep-learning (DL)-based MC denoising algorithms, as well as clinical tests involving more than 560 patient p...
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...
Authors: Tommaso Frigerio, Joshua Genender, John M. Hoffman, Catherine (Caffi) Meyer
Affiliation: UCLA, David Geffen School of Medicine at UCLA
Abstract Preview: Purpose: Accurate bone marrow segmentation is required for bone marrow dosimetry to monitor for dangers in PSMA-Lu177 radioligand therapy. We introduce a hybrid (AI/semantic knowledge) segmentation pi...
Authors: Leon Dunn
Affiliation: IsoAnalytics Pty. Ltd.
Abstract Preview: Purpose: The purpose of this work is to present the development and results of an automated Varian Trajectory Log file processing software platform called Sentinel (IsoAnalytics Pty. Ltd.).
Methods...
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: Hoyeon Lee
Affiliation: University of Hong Kong
Abstract Preview: Purpose: Deep-learning approaches are widely investigated for Cone-Beam CT (CBCT) scatter correction to improve the quality of the linear-accelerator mounted CBCT. This study aims to optimize the deep...
Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang
Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University
Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...
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...