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Results for "automated framework": 36 found

A Framework for Automated Selection of Dose-Volume Objectives to Improve Radiation-Induced Immune Suppression (RIIS)-Related Overall Survival (OS) Following Chemo-Radiotherapy

Authors: Gabriel Lucas Andrade de Sousa, Einsley-Marie Janowski, Cam Nguyen, Krishni Wijesooriya

Affiliation: Department of Radiation Oncology, University of Virginia, Department of Physics, University of Virginia

Abstract Preview: Purpose: Optimizing radiation therapy (RT) to spare the immune system may improve Overall Survival (OS) in cancer patients. This study develops a computational algorithm to identify optimal dose-volum...

A Monte Carlo Framework for Automated Quality Assurance of Dynamically Collimated Pencil Beam Scanning Clinical Treatment Deliveries

Authors: Laura Bennett, Wesley S. Culberson, Albert Du, Kevin J. Erhart, Ryan T. Flynn, Ryan Gardner, Alonso N. Gutierrez, Patrick M Hill, Daniel E. Hyer, Eric Jensen, Kaustubh A. Patwardhan, Blake R. Smith, Nhan Vu, Karsten K. Wake

Affiliation: University of Wisconsin, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Miami Cancer Institute, Baptist Health South Florida, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Ion Beam Applications (IBA), University of Iowa, Iowa Health Care, .decimal

Abstract Preview: Purpose: To develop and experimentally validate a novel Monte Carlo (MC) framework designed to enable calculation-based quality assurance (QA) for collimated intensity modulated proton therapy treatme...

A Multi-Agent Approach for Fully Automated Nephrometry Feature Extraction in CT

Authors: Matthew S Brown, Joshua Genender, John M. Hoffman, Gabriel Melendez-Corres, Muhammad W. Wahi-Anwar

Affiliation: David Geffen School of Medicine at UCLA, UCLA Department of Radiology

Abstract Preview: Purpose: Renal lesions are evaluated using scoring systems based on visual assessments and manual measurements. The purpose of this work is to develop a multi-agent system for automated anatomic landm...

A Novel Integrated Framework for Rapid Automatic Calculation of Organ Absorbed Dose from kV-CBCT Imaging during Radiotherapy

Authors: Marios Myronakis, Kyriaki Theodorou

Affiliation: Medical Physics Department, Medical School, University of Thessaly

Abstract Preview: Purpose: The development of an integrated application framework for rapid, seamless, and automated calculation of absorbed organ dose for individual patients undergoing kV CBCT imaging over the course...

A Semi-Automated Landmark Identification Framework for Liver MR-CT Image Pairs: Towards a Multi-Modality DIR Benchmark Dataset

Authors: Deshan Yang, Zhendong Zhang

Affiliation: Duke University, Department of Radiation Oncology, Duke University

Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...

AI-Driven Quality Assurance for Gamma Camera/SPECT Anomaly Detection Using Contrastive Learning

Authors: Shanli Ding, Osama R. Mawlawi, Tinsu Pan

Affiliation: UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Reliable detection of anomalies in Gamma Camera/SPECT flood images is vital for quality assurance (QA). Traditional methods relying on numerical thresholds and manual inspections often mis...

An Automated Solution to Staged Treatments for Arteriovenous Malformations in Gammaknife

Authors: Strahinja Stojadinovic, Robert Timmerman, Yulong Yan

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas Southwestern Medical Center, University of Texas Southwestern Medical Center

Abstract Preview: Purpose: Radiosurgery for large (>10cc) arteriovenous malformations (AVMs) poses significant challenges due to increased risks of complications and lower obliteration rates. To mitigate toxicity, larg...

Automated Framework for Predicting Tumour Growth in Vestibular Schwannomas Using Contrast-Enhanced T1-Weighted MRI

Authors: Mehdi Amini, Minerva Becker, Simina Chiriac, Alexandre Cusin, Dimitrios Daskalou, Ghasem Hajianfar, Sophie Neveu, Marcella Pucci, Yazdan Salimi, Pascal Senn, Habib Zaidi

Affiliation: Geneva University Hospital, Division of Radiology, Diagnostic Department, Geneva University Hospitals, Service of Otorhinolaryngology-Head and Neck Surgery, Department of Clinical Neurosciences, Geneva University Hospitals

Abstract Preview: Purpose: Personalized prediction of vestibular schwannoma (VS) tumour growth is crucial for guiding patient management decisions toward observation versus intervention. This study proposes an automate...

Automated Full-Body Tumor Segmentation from PET/CT Images

Authors: Austin Castelo, Xinru Chen, Caroline Chung, Laurence Edward Court, Jaganathan A Parameshwaran, Zhan Xu, Jinzhong Yang, Yao Zhao

Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
To develop a deep learning-based segmentation model to automatically delineate tumors from full-body PET/CT images.
Methods:
PET/CT image pairs of 91 patients were collected for this...

Automated Tool for Radiotherapy Initial Patient Setup: A Robust Approach Based on Vertebral Identification

Authors: Hailun Pan, Yingli Yang, Jie Zhang, Yibin Zhang

Affiliation: Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital, Department of Radiation Oncology, Ruijin Hospital, , Shanghai Jiaotong University School Of Medicine, Shanghai United imaging Healthcare Advanced Technology Research Institute

Abstract Preview: Purpose: Accurate patient positioning is critical in radiotherapy (RT) to ensure effective treatment delivery and minimize harming surrounding healthy tissues. Vertebral misalignment during RT setup h...

Automated Treatment Planning Script for Bone Metastases Using Eclipse TPS

Authors: Maria Jose Almada, Bruno Forti, Andres Lima, Carlos Daniel Venencia

Affiliation: Instituto Zunino - Fundacion Marie Curie

Abstract Preview: Purpose:
To automate the planning of radiotherapy treatments for bone metastases using a script in the ECLIPSE planning system version 15.6 with a graphical interface.
Methods:
A script was d...

Automating Radiographic Sharp Score Prediction in Rheumatoid Arthritis Using Multistage Deep Learning Methods

Authors: Hajar Moradmand, Lei Ren

Affiliation: University of Maryland School of Medicine, University of Maryland

Abstract Preview: Purpose:
The Sharp-van der Heijde (SvH) score is essential for assessing joint damage in rheumatoid arthritis (RA) from radiographic images. However, manual scoring is time-intensive and prone to v...

Beam Orientation Optimization in IMRT Using Sparse Mixed Integer Programming and Non-Convex IMRT Fluence Map Optimization

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...

Breastplan-Helper: Publicly Shared Source Scripting Toolset to Assist in 3D Breast Planning

Authors: Ryan Clark, Anthony Magliari, Luis Felipe Oliveira E Silva, Yang Sheng, Jason R Vickress, Qingrong Jackie Wu, Giulianne Rivelli Rodrigues Zaratim

Affiliation: Verspeeten Family Cancer Center, Office of Medical Affairs, Varian, A Siemens Healthineers Company, Confiar Radioterapia, Duke University Medical Center

Abstract Preview: Purpose: Develop a toolset to replace several of the tedious steps required to manually generate 3D breast treatment plans using static gantry forward planned tangent beams.

Methods: Eclipse Sc...

Contrastive Learning and Hybrid CNN-Transformer Model for Unpaired MR Image Synthesis in Acute Cerebral Infarction

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...

Cycle-Consistent Multi-Task Automated Segmentation and Synthetic CT Generation Model for Adaptive Proton Therapy

Authors: Derek Tang, Susu Yan

Affiliation: Massachusetts General Hospital

Abstract Preview: Purpose: To evaluate the performance of a multi-task automated-segmentation and synthetic CT generation model (sCT) and investigate its application in an adaptive proton therapy workflow.
Methods: ...

Deep Learning-Based Segmentation for Precision Radiation Therapy in Breast Cancertreatment

Authors: Hamdah Alanazi, Silvia Pella

Affiliation: FAU, Florida Atlantic University

Abstract Preview: Purpose: The appearance of breast cancer in the global list of most common cancers worldwide requires
research for ultimate treatment approaches including radiation therapy to reduce deaths from br...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

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...

Development and Validation of a Deep Learning-Based Auto-Segmentation Module for Vestibular Schwannoma

Authors: John Byun, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Xianghua Ye, Kangning Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Neurosurgery, Stanford University, Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: Accurate and automated delineation of vestibular schwannoma (VS) volume is crucial for disease management, as both treatment approaches (stereotactic radiosurgery and invasive surgery) and mo...

Development of a Comprehensive Thoracic Re-Irradiation Database and Investigation of Time-Dependent Dose-Recovery Dynamics for Toxicity Modeling

Authors: Victoria Doss, Tsion Gebre, Rachel B. Ger, Esi A Hagan, Elaina Hales, Russell K Hales, Xun Jia, Heng Li, Dezhi Liu, Todd R. McNutt, Meti Negassa, Anas Obaideen, Tinker Trent, K. Ranh Voong, Cecilia FPM de Sousa

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University

Abstract Preview: Purpose: As cancer care advances, more patients require re-irradiation, yet evidence-based data is lacking. This study aimed to develop a thoracic re-irradiation database and explore time-dependent re...

Development of a Quantitative Surface Mapping Analysis Framework Involving a Robust Mask Removal Algorithm for Improved Objective Patient Setup Assessment in Head and Neck Intensity Modulated Proton Therapy

Authors: Grant Evans, Maxwell Arthur Kassel, Charles Shang, Michael H. Shang, Stephen Shang, Timothy R Williams

Affiliation: South Florida Proton Therapy Institute, SFPRF, Department of Radiation Medicine, MedStar Georgetown University Hospital

Abstract Preview: Purpose:
Daily image guidance for head and neck intensity-modulated proton therapy (IMPT) presents significant challenges due to large target volumes and anatomical changes. Geometric deviations al...

Development of an Eclipse Scripting API-Based Toolbox for Automated Planning in Non-Small Cell Lung Cancer: Feasibility and Validation Study

Authors: Ming Chao, Hao Guo, Tenzin Kunkyab, Yang Lei, Tian Liu, Kenneth Rosenzweig, Robert Samstein, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
This study aims to develop and validate an Eclipse Scripting Application Programming Interface (ESAPI)-based planning toolbox that incorporates preset human expertise to improve planning e...

Dynamic Winston-Lutz Testing for FFF Beams

Authors: Cambridge L Bui-Nguyen, Alexander S. Nguyen, Liqiang (Lee) Tao

Affiliation: Varian AOS @Epic Care, UC Berkeley

Abstract Preview: Purpose: Dynamic Winston-Lutz (WL) testing provides a comprehensive framework for evaluating the accuracy of isocenter alignment. This study investigates the impact of dynamic beam modulation, such as...

Enhanced 3D Volumetric Denoising for Low-Dose CT Images Using Hformer

Authors: Edward Robert Criscuolo, Chenlu Qin, Deshan Yang, Zhendong Zhang

Affiliation: Duke University, Department of Radiation Oncology, Duke University

Abstract Preview: Purpose:
Low-dose CT (LDCT) imaging minimizes radiation exposure but introduces significant noise, compromising image quality. While deep learning-based denoising models such as HFormer achieve sta...

Fully Automated Zero-Shot Organ Segmentation in Male Pelvic MR Images for MR-Guided Radiation Therapy

Authors: Jihun Kim, Jin Sung Kim, Jun Won Kim, Yong Tae Kim, Chanwoong Lee, Jihyn Pyo, Young Hun Yoon

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Gangnam Severance Hospital, Yonsei University College of Medicine

Abstract Preview: Purpose: Although segmentation foundation models have recently demonstrated promising zero-shot performance on natural images, its clinical application to magnetic resonance (MR) images still requires...

Latent Diffusion Model-Driven Semi-Supervised Semantic Segmentation of Cell Nuclei

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

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

Abstract Preview: Purpose: Automated semantic segmentation of cell nuclei in microscopic images is vital for disease diagnosis and tissue microenvironment analysis. However, obtaining large annotated datasets for train...

Optimizing Motion Management QA: Clinical Integration of Aapm TG-306 for the Radixact Synchrony System

Authors: Hulya Ozdemir Buss, Jeffrey Geiger, Kim Howard, Julius G. Ojwang, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: The Radixact Synchrony system integrates real-time motion tracking and compensates to improve treatment accuracy for moving targets. This study presents a streamlined and efficient quality as...

Pancrea-Seg-Net: A Semi-Supervised Deep Learning Framework for Pancreatic Tumor and Vessel Segmentation

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...

Precision Radiotherapy Dose Prediction Using Foundation Model-Augmented Learning

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Xianjin Dai, PhD, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Artificial intelligence (AI)-driven methods have transformed dose prediction, streamlining the automation of radiotherapy treatment planning. However, traditional approaches depend exclusivel...

Prompt Preset for Imaging Physics Education and Board Style Question Generation: Development and Validation

Authors: Rose Al Helo, Shengwen Deng, Sven L. Gallo, David W. Jordan

Affiliation: Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center, University Hospitals Cleveland Medical Center, Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center; School of Medicine, Case Western Reserve University; Department of Radiology, Louis Stokes Cleveland VA Medical Center

Abstract Preview: Purpose: From an educator perspective, preparing test questions for trainees is time-consuming and requires a lot of quality verification steps (review of stems, distractors, referencing) that can pot...

Real-Time Fully Automated IMRT Planning without Optimization Process Using a Two-Step AI Framework

Authors: Daisuke Kawahara, Takaaki Matsuura, Yuji Murakami, Ryunosuke Yanagida

Affiliation: Hiroshima High-Precision Radiotherapy Cancer Center, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima

Abstract Preview: Purpose: In recent years, automation in radiation therapy planning using AI has gained significant attention to reduce the workload of treatment planners. Adaptive Radiation Therapy (ART), as a new fo...

Sources of Variability in Evaluating Ultrasound Imaging Performance Using Randomly-Distributed Hypoechoic Sphere Phantom

Authors: Cristel Baiu, Zheng Feng Lu, Dufan Wu, Baihui Yu

Affiliation: University of Wisconsin, Massachusetts General Hospital, University of Chicago

Abstract Preview: Purpose: IEC TS 62791:2022 specified a clinically meaningful and quantitative framework for evaluating diagnostic ultrasound performance by measuring the lesion signal-to-noise ratio (LSNR) using rand...

Standardized MRI-CT Hybrid Workflow for High-Dose-Rate Image-Guided Adaptive Brachytherapy in Cervical Cancer: Aapm TG-303 Implementation

Authors: Kim Creach, Kim Howard, Julius G. Ojwang, Richard A. Shaw, Neelu Soni

Affiliation: Mercy Hospital Springfield

Abstract Preview: Purpose: To present a standardized MRI-CT hybrid workflow for High-Dose-Rate (HDR) Image-Guided Adaptive Brachytherapy (IGBT) in cervical cancer, aligned with AAPM TG-303, as a model to assist with im...

Streamlining Hippocampal-Sparing Whole-Brain VMAT Planning: Enhancing Efficiency and Plan Quality with an Automated Workflow

Authors: Eric C. Ford, Yulun He, Minsun Kim, Dustin Melancon, Juergen Meyer, Dong Joo Rhee, Yinghua Tao

Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, MD Anderson Cancer Center, University of Washington

Abstract Preview: Purpose: To develop and evaluate an automated-planning technique capable of generating high-quality treatment plans for hippocampal-sparing-whole-brain radiation therapy.
Methods: An auto-planning ...

The Topas Monte Carlo Framework – Status and Outlook after 15 Years of Development

Authors: Alejandro Bertolet, Jorge Naoki Dominguez Kondo, Bruce A. Faddegon, Thongchai Masilela, Isaac Meyer, Victor V. Onecha, Harald Paganetti, Jose A. Ramos-Mendez, Jan PO Schuemann, Wook-Geun Shin

Affiliation: University of California San Francisco, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital

Abstract Preview: Purpose: To present the results of 15 years of developments of the TOPAS TOol for PArticle Simulation framework, and to highlight recent and new developments.

Methods: Fundamental understanding...

Unlocking Adaptive Radiotherapy Flexibility: Integrating Ethos Adaptive Therapy and Halcyon IGRT with Scripting Innovations

Authors: Min Geon Choi, Sean J. Domal, Ruiqi Li, Taoran Li, Mu-Han Lin, Yang Kyun Park, David D.M. Parsons, Justin D. Visak

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, University of Pennsylvania, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Ethos X-ray-guided online adaptive radiotherapy (ART) enables precise, daily adaptive treatments but requires significant resources, limiting widespread adoption. Many treatment sites do not ...