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Results for "integrated robust": 27 found

A Hybrid Radiomics-Integrated Machine Learning Framework for Early Identification of Potential Radiation Pneumonitis in Lung Cancer Patients

Authors: Christos Ilioudis, Marios Myronakis, Sotirios Raptis, Kyriaki Theodorou

Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Information and Electronic Engineering, International Hellenic University (IHU)

Abstract Preview: Purpose: This study presents a radiomics-driven, machine learning framework developed to predict the possibility of Radiation Pneumonitis (RP), as a side effect of radiation therapy in lung cancer pat...

A No-Reference Medical Image Quality Assessment Method Based on Automated Distortion Recognition Technology: Application to Preprocessing in MRI-Guided Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Yuan Tang, Zilin Wang, Guohua Wu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
To develop a novel no-reference image quality assessment (NRIQA) method for evaluating the effectiveness of image preprocessing in MRI-guided radiotherapy (MRIgRT), thereby enhancing clini...

An Integrated Robust Inverse Planning Based on AI-Built Dose Kernel Library for Preclinical Radio-Neuromodulation Using Focused Kv X-Rays

Authors: Wenbo Gu, Chenhui Qiu, Ke Sheng, Liyan Sun, Weiyuan Sun, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiology, Stanford University, University of Pennsylvania, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, Stanford University,

Abstract Preview: Purpose:
The small animal radio-neuromodulation platform developed in our previous work utilized focused kV x-ray beams rotating and translating in predefined trajectories to irradiate small, mm si...

Artificial Intelligence (AI)-Driven Automatic Contour Quality Assurance (QA) with Uncertainty Quantification

Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, 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: Accurate delineation of treatment targets and organs-at-risk is crucial for radiotherapy. Despite significant progress in artificial intelligence (AI)-based automatic segmentation tools, effi...

Automated MR Segmentation for Online Adaptive MR-Linac Therapy Using an in-House Model

Authors: David L. Barbee, David Byun, Matt Long, Jose R. Teruel Antolin, Michael J Zelefsky

Affiliation: NYU Langone Health

Abstract Preview: Purpose:
Online adaptive MR-Linac therapy requires contour adaptation, often adding 20 minutes to treatment time and reducing machine throughput. This study introduces a fully automated MR contour ...

Automated Quantification of Irradiation-Induced Effects on Ribosome Biogenesis Using Foundational AI Model and Image Analysis

Authors: Kyle J. Wang, Yading Yuan

Affiliation: Bergen County Technical High School, Columbia University Irving Medical Center, Department of Radiation Oncology

Abstract Preview: Purpose: Genotoxic cancer therapies inevitably damage normal cells, particularly circulating hematopoietic cells, posting a risk for therapy-induced leukemia. This study aims to develop an automated i...

Deep Learning Based Automatic Cerebrovascular Segmentation in Multi-Center TOF-MRA Datasets

Authors: Gayoung Kim, Junghoon Lee

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

Abstract Preview: Purpose: 3D time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for visualizing cerebrovascular structures. Accurate segmentation of cerebrovascular structures is critical for relia...

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 Fast Quality Assurance Software Tool for Helical Online Adaptive Radiation Therapy

Authors: Guang-Pei Chen, Mi Huang, Haidy G. Nasief, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Recently, kV imaging has been integrated into the Accuray Radixact platform, facilitating online adaptive and scan-plan-treat workflows with helical delivery in the near future. In order to s...

Dosinme: A 3D Visualization Platform for Internal Dosimetry and Radionuclide Behavior in Computational Human Phantoms

Authors: Lotem Buchbinder Shadur, Shaheen Dewji, Martin Graffigna, Alejandro Rafael Martinez, Emmanuel Mate-Kole, Antonio McClain, Samuel Taylor, Jeffrey Wang

Affiliation: Student, Nuclear and Radiological Engineering and Medical Physics Programs, Georgiaย Institute of Technology

Abstract Preview: Purpose: DosInMe is an internal dosimetry visualization tool developed by the Radiological Engineering, Detection, and Dosimetry Laboratory at Georgia Tech to assist researchers and professionals in v...

Efficient Robustness Optimization in Intensity Modulated Proton Therapy for Head and Neck Cancer Via Visual State Space Attention Generative Adversarial Networks (VSSA-GAN)

Authors: Nan Li, Yaoying Liu, Shouping Xu, Gaolong Zhang

Affiliation: Department of Radiation Oncology, School of Physics, Beihang University, School of physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose: In intensity-modulated proton therapy (IMPT) for head and neck cancer, CBCT registration ensures accurate setup, minimizing dose errors. Unlike IMRT, IMPT plans directly define tumor volumes ...

Feasibility of X-Ray Based Online Adaptive Dynamic Optimization with Integrated Knowledge-Based Planning for Head and Neck Cancer

Authors: Jacob S. Buatti, Mu-Han Lin, Dominic Moon, David D.M. Parsons, David Sher, Justin D. Visak, Hui Ju Wang

Affiliation: 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, Dallas, TX

Abstract Preview: Purpose: Most current adaptive treatment planning systems (TPS) natively utilize static planning goals from the reference plan for online adaptive re-optimization. In complex head-and-neck cancer (HNC...

Foundation Model Guidance for CBCT-CT Image Registration in Radiotherapy

Authors: Hacene Azizi, Abderaouf Behouch, Nabil Maalej, Aamir Raja, Mohamed Lamine Seghier

Affiliation: Khalifa University Biomedical Engineering & Biotechnology, Laboratory of dosing, analysis and characterization in high resolution, Ferhat Abbas Setif 1 University, Khalifa University Physics Department, Khalifa University

Abstract Preview: Purpose:
To ensure accurate alignment of cone-beam computed tomography (CBCT) and computed tomography (CT) images for image-guided radiotherapy, this study evaluates a foundation model guidance fra...

Improving Mammography Diagnosis Accuracy through Global Context and Local Lesion Integration

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...

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 Clinical Knowledge Via Llms for Precise Organ-at-Risk Segmentation in Pancreatic Cancer SBRT

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...

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...

Multi-Organ Segmentation of Pelvic Cone-Beam Computed Tomography (CBCT) with Transformer Models to Enhance Adaptive Radiotherapy for Prostate Cancer

Authors: Ming Chao, Thomas Chum, Tenzin Kunkyab, Yang Lei, Tian Liu, Richard G Stock, Hasan Wazir, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
This study aims to develop effective strategies for multi-organ segmentation of pelvic cone-beam computed tomography (CBCT) images based on transformer models to facilitate adaptive radiat...

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...

Refining the in-House Modified COMS Eye Plaque Workflow

Authors: Vishruta A. Dumane, Andrew Lukban, Kiran Pant, Charlotte Elizabeth Read, Ren-Dih Sheu, Nadia M. Vassell

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

Abstract Preview: Purpose: This work introduces a refined in-house modified COMS eye plaque management system to streamline processes, reduce redundancies, and enhance usability.
Methods: A web-based application wit...

Reliable Markerless Lung Tumor Tracking with Built-in Patient-Specific Quality Assurance

Authors: Weixing Cai, Laura I. Cervino, Qiyong Fan, Yabo Fu, Tianfang Li, Xiang Li, Jean M. Moran, Hai Pham, Pengpeng Zhang

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: AAPM Task Group Report 273 emphasizes the importance of rigorous validation to ensure the generalizability and robustness of machine learning-based clinical tools before their implementation ...

SPECT/CT Multimodal Segmentation of Bone Marrow for Theranostic Dosimetry

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...

Simulation Design of a Dedicated Head Coil for Enhanced EPT Imaging to Map the Electrical Properties of Tumor Tissues

Authors: Jingyao Chen, Yingli Yang, Jie Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Ruijin Hospital, Shanghai United imaging Healthcare Advanced Technology Research Institute

Abstract Preview: Purpose: Magnetic Resonance Electrical Properties Tomography (MR EPT) is a method to spatially mapping the conductivity and permittivity based on small B1 field changes after the imaged object was int...

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 ...

Towards Real-Time Radiotherapy Monitoring By Cherenkov Imaging: Applications of Patient-Specific Bio-Morphological Features Segmented Via Deep Learning

Authors: Petr Bruza, Yao Chen, David J. Gladstone, Lesley A Jarvis, Brian W Pogue, Kimberley S Samkoe, Yucheng Tang, Shiru Wang, Rongxiao Zhang

Affiliation: NVIDIA Corp, Dartmouth College, Thayer School of Engineering, Dartmouth College, Dartmouth Cancer Center, University of Missouri, University of Wisconsin - Madison

Abstract Preview: Purpose: Cherenkov imaging provides real-time visualization of megavoltage radiation beam delivery during radiotherapy. Patient-specific bio-morphological features, such as vasculature, captured in th...

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...

Weakly Supervised Spatial Implicit Neural Representation Learning for 3D MRI-Ultrasound Deformable Image Registration in HDR Prostate Brachytherapy

Authors: Michael Baine, Yang Lei, Yu Lei, Ruirui Liu, Tian Liu, Jing Wang

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

Abstract Preview: Purpose: Accurate 3D deformable registration of MRI and ultrasound (US) is essential for real-time image guidance during high-dose-rate (HDR) prostate brachytherapy. However, MRI-US registration of th...