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Results for "bio features": 12 found

A Clinically Aligned Embedding Model for Glioma Prognostication Via Radiology-Pathology Report Matching

Authors: Steve Braunstein, Yannet Interian, Hui Lin, Bo Liu, Janine Lupo, Olivier Morin, Benedict Neo

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Data Science, University of San Francisco, University of San Francisco

Abstract Preview: Purpose: Large Language Models (LLMs) demonstrate strong general text comprehension but remain limited in oncology due to insufficient contextual alignment. We pilot embedding alignment through radiol...

A Radiomic Quantification Framework for Hyperparameter Optimization in Texture Characterization

Authors: Yuli Lu, Chendong Ni, Cheng Qian, Kun Qian, Weiwei Sang, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Haiming Zhu

Affiliation: Jiahui International Hospital, Radiation Oncology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: To develop a radiomic quantification framework to evaluate the effects of radiomic image preprocessing hyperparameters (i.e., image resampling and discretization) on texture characterization ...

A Vision-Language Deep Learning Model for Predicting Survival Outcomes in Glioblastoma Patients

Authors: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan

Affiliation: Emory University and Winship Cancer Institute, Emory University, Georgia Institute of Technology, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...

BEST IN PHYSICS MULTI-DISCIPLINARY: Building a Cross-Modality Model to Integrate Bio-Clinical Features, Anatomical MRI, and White-Matter Pathlength Mapping for Personalized Glioblastoma RT Planning

Authors: Steve Braunstein, Angela Jakary, Hui Lin, Bo Liu, Janine Lupo, Tiffany Ngan, Ke Sheng, Nate Tran

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Radiology and Biomedical Imaging, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Current RT clinical target volumes (CTVs) for Glioblastoma (GBM) employ 2cm isotropic expansions of gross tumor volumes. However, studies showed patients still experience progression beyond t...

Centralizing Resources with a Microsoft-Based Wiki Platform: Enhancing Collaboration and Efficiency in Radiation Oncology

Authors: Simon Brundage, Jiajin Fan, Ulrich Langner, Qiongge Li, Jian Liu, Wei Nie, Edwin Quashie, Xiaofeng Zhu

Affiliation: Brown University Health, Hofstra University Medical Physics Program, Inova Hospital, Inova Schar Cancer Institute, Indiana University School of Medicine, Department of Radiation Oncology

Abstract Preview: Purpose:
Managing departmental policies, clinical protocols, QA procedures, workflows, and troubleshooting documentation is critical in radiation oncology. A Microsoft-based wiki platform was devel...

Developing a Dataset for Investigations into the Impact of CT Acquisition and Reconstruction Conditions on Quantitative Imaging Using Paired Image Quality and Radiomics Phantom Data

Authors: Morgan A. Daly, David J. Goodenough, Andrew M. Hernandez, John M. Hoffman, Joshua Levy, Michael F. McNitt-Gray, Ali Uneri, Bino Varghese

Affiliation: University of California, George Washington University, David Geffen School of Medicine at UCLA, Johns Hopkins Univ, University of Southern California, The Phantom Laboratory

Abstract Preview: Purpose: Quantitative imaging is affected by CT acquisition and reconstruction conditions, limiting robustness in multi-site or -scanner studies. This work aimed to develop a dataset that will enable ...

Enhancing Medical Physics Education: From Student Needs to a Moodle-Based LMS

Authors: Paul B. Ravindran

Affiliation: Christian Institute of Health Sciences and Research

Abstract Preview: Purpose: In the past decades, Master's programs in Medical Physics in India have made significant strides, though many have faced challenges in accessing adequate resources for didactic lectures and p...

Feasibility of Developing a Radiomic Fingerprint to Predict Pulmonary Embolism Clot Types to Aid in Determining Intervention for Intermediate-Risk Patients.

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...

Graph-Based Feature Selection to Improve Stability and Reproducibility of CT-Based Radiomics in Head and Neck Squamous Cell Carcinoma: A Cross-Institutional Study

Authors: Daria Gaykalova, Ranee Mehra, Jason K Molitoris, Hajar Moradmand, Lei Ren, Amit Sawant, Phuoc Tran

Affiliation: University of Maryland School of Medicine, Maryland University Baltimore, University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Radiomics extracts quantitative imaging biomarkers from medical images. However, maintaining the reproducibility and stability of selected features across institutions and parameter settings ...

Opentps: An Open-Source Radiotherapy Treatment Planning System to Foster Research, Innovation, and Education in Medical Physics

Authors: Ana Maria Barragan Montero, Damien Dasnoy, Sylvain Deffet, Valentine Dormal, Colin Gaban, Melanie Ghislaine, Valentin Hamaide, Guillaume Janssens, John A. Lee, Eliot Peeters, Danah Pross, Luciano Rivetti, Benjamin Roberfroid, Romain Schyns, Kevin Souris, Edmond S. Sterpin, Sophie Wuyckens

Affiliation: Ion Beam Applications SA, Hospital Riviera-Chablais, UCLouvain, Multitel, UniversitΓ© Catholique de Louvain, IBA, Faculty of Mathematics and Physics, University of Ljubljana, Universite Catholique de Louvain

Abstract Preview: Purpose: Treatment planning systems (TPSs) are essential for simulating and optimizing radiotherapy treatments. However, clinical TPSs are expensive software commercialized by private companies and of...

Patient-Specific Bio-Morphological Features in Cherenkov Imaging for Positioning Verification: A Retrospective Analysis in Accelerated Partial Breast Irradiation (aPBI) VMAT Radiotherapy

Authors: Yao Chen, Lesley A Jarvis, Allison Matous, Rongxiao Zhang

Affiliation: Dartmouth College, University of Missouri, Dartmouth Cancer Center, Dartmouth Health

Abstract Preview: Purpose: Precise patient positioning is critical in accelerated partial breast irradiation (aPBI) to ensure accurate dose delivery to the tumor bed while minimizing exposure to surrounding healthy tis...

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...