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Results for "level gpu": 16 found

A Recent Evaluation on the Performance of Llms on Radiation Oncology Physics Using Questions of Randomly Shuffled Options

Authors: Dequan Chen, Jason Michael Holmes, Tianming Liu, Wei Liu, Zhengliang Liu, Jiajian Shen, Peilong Wang

Affiliation: Department of Radiology, Mayo Clinic, Department of Radiation Oncology, Mayo Clinic, School of Computing, University of Georgia

Abstract Preview: Purpose:
We present a study to evaluate the performance of large language models (LLMs) in answering radiation oncology physics questions, focusing on the recently released models.
Methods:
A...

Augmenting Histopathology Lymphocyte Detection with Gpt-4 in-Context Visual Reasoning

Authors: Kyle J. Lafata, Casey Y. Lee, Xiang Li, Megan K. Russ, Zion Sheng

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose:
Traditional deep learning-based cell segmentation models face limitations, such as the need for extensive training data and retraining when encountering new cell types or domains. This stu...

CT-Free PET Imaging: Synthetic CT Generation for Efficient and Accurate PET-Based Planning

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang

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

Abstract Preview: Purpose:
PET is used in radiotherapy workflows for accurate target delineation. However, a separate CT scan is typically required for attenuation correction in PET imaging and for registering PET-d...

Clinical Implementation of a Film Based Psqa System for SBRT on a 1.5T MR-Linac

Authors: Dylan Yamabe Breitkreutz, Lee Chin, Brige P. Chugh, Mark D'Souza, Brian M. Keller, Anthony Kim, Michelle K. Nielsen, Arjun Sahgal

Affiliation: Sunnybrook Health Sciences Centre

Abstract Preview: Purpose: The Elekta Unity MR-linac delivers highly conformal SBRT treatments using IMRT. These treatment plans require patient-specific quality assurance (PSQA) measurements to detect discrepancies be...

Comparative Analysis of Soft Tissues and 3D Printing Materials Using Euclidean Distance for Linear Attenuation Coefficient

Authors: Gisell Ruiz Boiset, Paulo ROBERTO Costa, Elsa Bifano Pimenta

Affiliation: University of São Paulo (USP), Institute of Physics

Abstract Preview: Purpose: This study evaluates the similarity between the linear attenuation coefficients of soft tissues and 3D printing materials in diagnostic imaging range using the Euclidean distance approach.

Evaluation of a Novel Multimodal Deformable Image Registration Algorithm for Pelvic MRI-CT Fusion in Radiotherapy

Authors: Christian Fiandra, Marco Fusella, Gianfranco Loi, Silvia Pesente, Lorenzo Placidi, Claudio Vecchi, Orlando Zaccaria, Stefania Zara

Affiliation: Abano Terme Hospital, University of Turin, Maggiore della Carità, Tecnologie Avanzate Srl, Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Abstract Preview: Purpose: Deformable-image-registration (DIR) is essential in modern radiotherapy for adaptive RT, re-irradiation, and other clinical applications. Multimodal DIR is especially important in MRI-only wo...

First Demonstration of Prostate Radiotherapy Plan Optimization on an IBM Quantum Computer

Authors: Keisuke Fujii, Masahiro Kitagawa, Arezoo Modiri, Yuichiro Nakano, Ken N. Okada, Robabeh Rahimi, Akira SaiToh, Amit Sawant, Satoyuki Tsukano, Baoshe Zhang

Affiliation: University of Maryland, University of Maryland in Baltimore, Department of Computer and Information Sciences, Sojo University, Center for Quantum Information and Quantum Biology, Osaka University, Maryland University Baltimore, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Fully personalized radiotherapy requires computational resources far exceeding those of conventional CPU/GPU systems. This study explores the use of quantum computing (QC) in radiotherapy pla...

Frameless and Maskless Stereotactic Radiosurgery: Evaluating a Novel Robotic Head Motion Compensation Device

Authors: Michelle Alonso-Basanta, Carl Denis, Wenbo Gu, Xinmin Liu, Ahmad Sakaamini, Rodney D. Wiersma

Affiliation: UCLA, University of Pennsylvania, CDR Systems

Abstract Preview: Purpose: Stereotactic radiosurgery (SRS) is a non-invasive technique used to treat functional abnormalities and small brain tumors. Traditional SRS relies on a rigidly fixed metal head ring, causing d...

Gpt-Radplan: An Eclipse TPS Plugin for Automated Treatment Planning Based on Large Language Models

Authors: Peng Dong, Elizabeth Kidd, Sheng Liu, Thomas R. Niedermayr, Oscar Pastor-Serrano, Lei Xing, Yong Yang, James Zou

Affiliation: Department of Biomedical Data Science, Stanford University, Department of Radiation Oncology, Stanford University, Stanford University

Abstract Preview: Purpose: Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires iterative adjustments of optimization parameters to balance conflicting objectives. In thi...

Memory-Efficient Deep Learning for Volumetric Cone-Beam CT Image Reconstruction

Authors: Ziqi Gao, Lei Xing, Siqi Ye, S. Kevin Zhou

Affiliation: Department of Radiation Oncology, Stanford University, University of Science and Technology of China (USTC)

Abstract Preview: Purpose: To address the challenge of high memory usage in volumetric cone-beam CT (CBCT) imaging, we propose a method that combines joint reconstruction and super-resolution for sparsely sampled CBCT ...

Personalized and Automated Head & Neck Radiotherapy Planning with AI-Guided Optimization

Authors: Michael Bowers, Patrik Brodin, Madhur Garg, Rafi Kabarriti, William P. Martin, Todd R. McNutt, Julie Shade, Wolfgang A. Tomé, Christian Velten

Affiliation: Johns Hopkins University, Oncospace, Inc., Montefiore Medical Center

Abstract Preview: Purpose: Development of an automated planning tool utilizing AI generated patient-specific dose-volume histogram predictions for rapid H&N plan generation.
Methods: Planning best-practices were dev...

Predicting Brain V60% in Linac-Based Single-Isocenter-Multiple-Targets (SIMT) Stereotactic Radiosurgery Using Machine Learning

Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...

Prospective Organ-Level Dose Estimation in CT Imaging Using Scout-Net: A Comparison with Established Methods

Authors: Maria Jose Medrano, Grant Stevens, Liyan Sun, Justin Ruey Tse, Adam S. Wang, Sen Wang

Affiliation: Department of Radiology, Stanford University, GE HealthCare, Stanford University

Abstract Preview: Purpose: Patient exposure to ionizing radiation is a major concern in CT imaging. Size-specific dose estimation methods can prospectively estimate organ-level radiation doses based on patient sizes an...

Two Radiochemical Monte Carlo Models to Investigate the Radical Yields Under Proton Flash Irradiations

Authors: Yujie Chi, Yao Hao, Xun Jia, Youfang Lai, Yuting Peng, Francisco Javier Reynoso, Lingshu Yin, Tianyu Zhao, Xiandong Zhao

Affiliation: Johns Hopkins University, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Physics, University of Texas at Arlington, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, University of South Florida

Abstract Preview: Purpose: FLASH radiation therapy has shown remarkable tissue sparing effects compared to radiation therapy at conventional dose rates (CDR). Yet, its mechanism remains unclear. Radical production modu...

Ukan Architecture for Voxel-Level Dose Prediction in Radiotherapy

Authors: Lu Jiang, Ke Sheng

Affiliation: Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose:
Conventional radiotherapy treatment planning is guided by a set of generic objectives that are unspecific to patient anatomy. Treatment planning thus heavily relies on the planner’s experi...

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

Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, Peopleʼs Republic of China

Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...