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Results for "computational efficiency": 26 found

A Deep Learning-Based Method for Rapid Generation of Spot Weights in Single Field Optimization for Proton Therapy in Prostate Cancer

Authors: Yu Chang, Mei Chen

Affiliation: Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine

Abstract Preview: Purpose: Spot weights optimization, as a critical step in the proton therapy, is often time-consuming and labor-intensive. Deep learning, with its powerful learning and computational efficiency, can e...

A Novel Multi-Material Decomposition Algorithm for Improved Material Quantification Using Dual-Energy CT

Authors: Dale Black, David Clymer, Huanjun Ding, Hamidreza Khodajou Chokami, Sabee Molloi, Christine Vy Nguyen, Tim Sananikone, Alireza Shojazadeh, Randy Wang

Affiliation: Department of Radiological Sciences, University of California, University of California, Department of Radiological Sciences, University of California, Irvine, Department of Radiological Sciences, University of California, Irvine

Abstract Preview: Purpose: We present a novel multi-material decomposition (MMD) algorithm for accurate quantification of material concentration in reconstructed dual-energy CT images. This method addresses limitations...

A Novel Optimization Algorithm That Improves DVH Based Planning for Direction Modulated Brachytherapy Tandem Applicator.

Authors: Christopher L. Deufel, Suman Gautam, William Y. Song

Affiliation: Virginia Commonwealth University, Mayo Clinic

Abstract Preview: Purpose: Direction modulated brachytherapy creates anisotropic dose distribution from an isotropic source. This study aims to develop a truncated conditional value at risk optimization algorithm for D...

Advancing Post-Radiotherapy Toxicity Extraction: A Novel Privacy-Preserving, Parameter-Efficient Language Model Fine-Tuning

Authors: Hassan Bagher-Ebadian, Indrin J. Chetty, Mohamed Elshaikh, Ahmed I Ghanem, Mohammad M. Ghassemi, Reza Khanmohammadi, Benjamin Movsas, Shayan Siddiqui, Kundan S Thind, Jawad Turfa

Affiliation: Michigan State University, Department of Radiation Oncology,Cedars-Sinai Medical Center, 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: Extracting late radiotherapy-induced toxicities from free-text notes using natural language processing is complicated by negative symptom identification, computational demands, and data priva...

An Efficient Deep Learning Model with Multi-Scale Integration for Automated Pancreas Segmentation on MR Images

Authors: Jingyun Chen, Yading Yuan

Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology

Abstract Preview: Purpose: To develop and evaluate the Scale-attention network (SANet) for automated pancreas segmentation on MR images.
Methods: To develop SANet, we extended the classic U-Net design with a dynamic...

An Ultra-High Parallel Performance (UHPP) Framework for Highly Complex Radiotherapy Planning

Authors: Lu Jiang, Shusen Jing, Qihui Lyu, Dan Ruan, Ke Sheng, Qifan Xu

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

Abstract Preview: Purpose: In radiotherapy, the conformity and compactness of dose distribution are vital to patient outcomes. The introduction of highly complex planning, such as 4Ο€ radiotherapy, has provided a system...

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...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Brain Structural Covariance Networks in Nicotine-Dependent Users: A Graph Analysis

Authors: Humberto Monsivais, Brian A. Taylor, Francesco Versace

Affiliation: Purdue University, Department of Behavioral Science, Division of Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: To identify possible signatures of altered brain morphometry in nicotine-dependency via a structural covariance network approach.

Methods: Fifty-one healthy controls (HC:27M, mean age=...

CNN-Based Reconstruction for 3D Scintillation Dosimetry of Proton Pencil Beams

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 ...

Comparative Analysis of Nine Deep Learning Architectures for Variable Density Grappa 1H Magnetic Resonance Spectroscopy Imaging (MRSI) Reconstruction

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 ...

Compressed Radiotherapy Treatment Planning (CompressRTP): A New Paradigm for Rapid and High-Quality Treatment Planning Optimization

Authors: Gourav Jhanwar, Mojtaba Tefagh, Masoud Zarepisheh

Affiliation: The University of Edinburgh, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose:
Radiotherapy treatment planning involves solving computationally-intensive and time-consuming optimization problems. Central to these problems is a large matrix known as the dose-influence...

Conversion Coefficients from Hp(10) to Organ and Effective Doses for Medical Staff Involved in Fluoroscopically Guided Interventional Procedures

Authors: Stephen Balter, Haegin Han, Cari M Kitahara, Taeeun Kwon, Choonsik Lee, Martha S Linet, Donald L. Miller

Affiliation: Columbia University Medical Center, National Cancer Institute, Food and Drug Administration

Abstract Preview: Purpose: Staff in fluoroscopically guided interventional (FGI) procedures are exposed to radiation. Inhomogeneous radiation fields and variability in procedural conditions make it challenging to deriv...

Development and Clinical Validation of a Tissue Maximum Ratio (TMR)-Based Monitor Units Second Check Script for Dynamic Conformal-Based Hyperarc Brain Radiosurgery Plans Via Scatter Correction Factors

Authors: Jacob Gooslin, Ellis Lee Johnson, Damodar Pokhrel

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, University of Kentucky, Radiation Medicine

Abstract Preview: Purpose: HyperArc radiosurgery permits treatment of multiple brain lesions using a single-isocenter improving treatment planning efficiency and workflow. A key stereotactic planning aspect is an indep...

Development of an Innovative and Efficient KBP-Based Automated Method for IMRT Optimization

Authors: Somayeh Gholami, Saeedeh Ketabi, Jeremy Kunz, Ali Yousefi

Affiliation: Department of Radiation Oncology, University of Utah, University of Utah, Department of Management- Operations Research, University of Isfahan

Abstract Preview: Purpose: This paper aims to present a novel approach for automatic knowledge-based planning optimization for Intensity Modulated Radiotherapy, along with the two downsizing techniques for improving th...

Feasibility Study on Creating a Digital Twin of Digital Subtraction Angiography Data Utilizing Monte Carlo and Computational Fluid Dynamic Simulations

Authors: Ciprian N. Ionita, Parisa Naghdi, Ahmad Rahmatpour

Affiliation: University at Buffalo, SUNY: University at Buffalo

Abstract Preview: Purpose: Quantitative angiography (QA) evaluates neurovascular hemodynamics, but is affected by X-ray parameters, vessel foreshortening, and imaging chain factors like detector efficiency, pixel size,...

GPU-Accelerated Beamlet and Full Dose Calculations for Efficient Radiation Therapy Planning

Authors: Girish Bal, Jan Kralj, Ayan Mitra, PhD, Ling Shao, Matjaz Subic, Yevgen Voronenko

Affiliation: RefleXion Medical, Cosylab

Abstract Preview: Purpose: This work enhances the efficiency of radiation therapy treatment planning by optimizing the beamlet dose matrix and full patient dose computations using GPU acceleration. The Collapsed-Cone C...

Implementing a Learning-to-Optimize Machine Learning Framework to Accelerate VMAT Treatment Planning Optimization for Prostate Cancer

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...

Log File-Based Patient-Specific QA As a Viable Alternative to Measurement-Based QA in IMPT

Authors: Sina Mossahebi, Pouya Sabouri, Kayla Schneider, James W Snider

Affiliation: University of Maryland School of Medicine, Proton International, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiation Oncology, University of Arkansas for Medical Sciences

Abstract Preview: Purpose:
Conventional patient-specific QA (PSQA) for intensity-modulated proton therapy (IMPT) requires extensive measurements, straining resources in single-room proton centers. This study evaluat...

Mitigating Discrepancies in Radiology Reports: A Robust LLM Approach for Generating Consistent Impressions

Authors: Junwen Liu, Mengzhen Wang, Ning Wen, Jifeng Xiao, Fuhua Yan, Yanzhao Yang, Xuekun Zhang, Zheyu Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai Jiaotong University, The SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai Jiaotong University Schoo of Medicine

Abstract Preview: Purpose:This study aims to develop and evaluate a large language model (LLM) fine-tuned to generate consistent and accurate impressions from imaging findings. Additionally, the study investigates the ...

Optimizing Atlas Counts for MRI-Guided Atlas-Based Autosegmentation of Swallowing Muscles in Head and Neck Radiotherapy

Authors: Zayne Belal, Rachel Drummey, Clifton David Fuller, Stephen Y. Lai, Brigid A. McDonald, Setareh Sharafi, Sonja Stieb, Kareem Abdul Wahid

Affiliation: Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Hospital of the University of Pennsylvania, Department of Radiology, Johns Hopkins University, KSA-KSB, Cantonal Hospital Aarau, College Of Osteopathic Medicine, NOVA Southeastern University, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
Radiotherapy-induced dysphagia can significantly impair head and neck (H&N) cancer patients’ quality of life. Despite the dose-dependent relationship between radiotherapy and dysphagia, sw...

Rectangular Aperture-Based Beam Orientation Optimization for 4Ο€ Non-Coplanar Small Animal IMRT Delivery

Authors: Dante PI Capaldi, Lu Jiang, Qihui Lyu, 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:
Preclinical small animal studies help understand radiation-induced biological responses, toxicities, and mechanisms, facilitating the translation of new therapies to patient treatment. Int...

Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

Authors: Yizheng Chen, Md Tauhidul Islam, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
Biomedical image segmentation (BIS) is a cornerstone of medical physics, enabling accurate delineation of anatomical structures and abnormalities, which is critical for diagnosis, treatmen...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu

Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...

Supercomputing-Enabled CT Virtual Imaging Trials: A Population-Scale Pilot Study

Authors: Ehsan Abadi, Zakaria Aboulbanine, Nicholas D Felice, David Fenwick, Anuj J. Kapadia, Cindy Marie McCabe, Jayasai Ram Rajagopal, Ehsan Samei

Affiliation: Duke University, Oak Ridge National Laboratory, Center for Virtual Imaging Trials, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose:
Virtual imaging trials (VITs) offer a computational alternative to clinical imaging trials leveraging virtual patients, scanners, and interpreters to assess imaging questions. To provide m...

Using a Generative Adversarial Network (GAN) for Source Particle Generation in Monte Carlo Radiation Therapy Simulations

Authors: Jiankui Yuan, Dandan Zheng, Tingliang Zhuang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, University of Rochester, Varian Medical Systems, Advanced Oncology Solutions

Abstract Preview: Purpose: In Monte Carlo (MC) radiation therapy dose calculations, latent variance exists when directly applying phase-space files (PSF) with a finite number of source particles, while the latter is pr...