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Results for "task specific": 52 found

4D CBCT Dynamic Images Recovery Using a 4D Neural Network

Authors: Ziheng Deng, Yao Hao, Runping Hou, Deshan Yang, Jun Zhao, Yufu Zhou

Affiliation: Department of Radiation Oncology, Duke University, School of Biomedical Engineering, Shanghai Jiao Tong University, Washington University School of Medicine, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: 4D CBCT has been developed to provide dynamic images for image-guided radiation therapy. However, as projection data are sorted into sparse and clustered phase-specific bins, 4D CBCT images a...

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 Dynamic Reconstruction and Motion Estimation Framework for Cardiorespiratory Motion-Resolved Real-Time Volumetric MR Imaging (DREME-MR)

Authors: Jie Deng, Xiaoxue Qian, Hua-Chieh Shao, 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: Based on a 3D pre-treatment MRI scan, we developed DREME-MR to jointly reconstruct the reference patient anatomy and a data-driven, patient-specific cardiorespiratory motion model. Via a moti...

A Novel Device for Radiation Therapy Machine Quality Assurance

Authors: Jonathan Dowell, Grace Francis, Wei Luo, Shane McCarthy, Janelle A. Molloy, Markus Murphy

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Iridesce Solutions, Inc.

Abstract Preview: Purpose: A novel radiation therapy quality assurance (RT QA) device has been designed, constructed and tested. The nüFilmTM machine QA system provides a method for collecting light, mechanical and rad...

A Tumor Tracking Method in Surface-Guided Radiotherapy

Authors: Penghao Gao, Zejun Jiang

Affiliation: Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences

Abstract Preview: Purpose: Real-time tumor tracking can effectively compensate for the impact of respiratory motion on dose distribution. We propose a patient-specific external-internal correlation model driven by opti...

Analysis of Inter-Organ Noise Variability for Clinical CT Images across 3133 Image Series

Authors: Lavsen Dahal, Francesco Ria, Ehsan Samei, Justin B. Solomon, Liesbeth Vancoillie, Yakun Zhang

Affiliation: Duke University, Carilion Clinic, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose: Clinical diagnostic task-based optimization of CT procedures require precise and organ-specific assessments. This study investigates inter-organ noise variability to highlight the limitations...

Assessing Accessibility for the Visually Impaired in Medical Physics Training

Authors: Lily Jo Bertemes, Careesa Billante, Ashley Cetnar, Maximilian Stephen Meineke, Runhe Tan

Affiliation: The Ohio State University James Cancer Hospital, The James Cancer Center, The Ohio State University, The Ohio State University - James Cancer Hospital

Abstract Preview: Purpose: Accessibility is a topic of increasing importance in many fields, and medical physics is no exception. While the traditional educational pathway presents a plethora of challenges for the visu...

Assessment of Off-Target Dose for Curative Treatment of Pregnant Head and Neck Cancer Case: A Monte-Carlo Study

Authors: Brianna Baek, David J. Carlson, Zhe (Jay) Chen, Dae Yup Han, Bon Tack Koo, Hyojun Park

Affiliation: Columbia University, Canyon Crest Academy, Department of Therapeutic Radiology, Yale University School of Medicine, Department of Radiation Oncology, Chung-Ang University Gwang Myeong Hospital

Abstract Preview: Purpose: To find an optimized treatment technique and shielding design for minimizing the dose to a fetus, a Monte-Carlo simulation was performed to evaluate the dosimetric contribution.
Methods: G...

Automating Protocol-Specific Chart Checking in Radiotherapy

Authors: Jiajin Fan, Ulrich Langner, Qiongge Li, Jian Liu, Wei Nie, Edwin Quashie

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:
Chart checking in radiotherapy ensures treatment plans meet clinical and safety standards. For patients in clinical trials, protocol-specific requirements add complexity, making manual rev...

BEST IN PHYSICS IMAGING: Dosimetric Impact of Iodinated Contrast Agent on Fibroglandular Tissue in Contrast-Enhanced Digital Mammography

Authors: Hannah Grover, Andrew J. Sampson

Affiliation: Oregon Health & Science University, UT Health San Antonio

Abstract Preview: Purpose: The goal of this work was to quantify the dosimetric impact of iodinated contrast on fibroglandular breast tissue to better inform clinical risk and benefit assessments when determining the m...

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...

Can AI-Based Llms be Your Study Buddy for ABR Professional Exams?

Authors: Arjit K. Baghwala, Sunan Cui, Jessica Fagerstrom, Eric C. Ford, Kristi Rae Gayle Hendrickson, Sharareh Koufigar, Samuel Ming Ho Luk, Bishwambhar Sengupta, Afua A. Yorke

Affiliation: University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, University of Vermont Medical Center, University of Washington and Fred Hutchinson Cancer Center, Houston Methodist Hospital

Abstract Preview: Purpose: The global burden of cancer continues to rise, leading to an increased workload in radiation oncology clinics. This surge is not only due to the growing demand for treatment machines and moda...

Chat with Oncology Information System Via Large Language Model

Authors: Michael Dohopolski, Xuejun Gu, Hao Jiang, Steve B. Jiang, Christopher Kabat, Jingying Lin, Weiguo Lu, Michael Tang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Neuralrad LLC, 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: To streamline access to clinical data stored in Oncology Information Systems such as MOSAIQ or ARIA, we developed an AI-powered chatbot capable of querying, summarizing, and interactively ans...

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 Plan Quality Prediction for Gamma Knife Radiosurgery of Brain Metastases

Authors: Chih-Wei Chang, Runyu Jiang, Mark Korpics, Yuan Shao, Aranee Sivananthan, Zhen Tian, Ralph Weichselbaum, Xiaofeng Yang, Aubrey Zhang, Xiaoman Zhang

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Department of Physics, University of Chicago, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, School of Public Health, University of Illinois Chicago

Abstract Preview: Purpose: Gamma Knife (GK) plan quality can vary significantly among planners, even for cases handled by the same planner. Although plan quality metrics such as coverage, selectivity, and gradient inde...

Developing Patient-Specific Functional Atlases with Inverse Distance Weighting of MR Images

Authors: Chibawanye I. Ene, Sherise D. Ferguson, Ping Hou, Vinodh A. Kumar, Ho-Ling Anthony Liu, Kyle R. Noll, Sujit S. Prabhu, Jian Ming Teo, Max Wintermark

Affiliation: Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
Functional brain atlases are used to guide clinical functional MRI (fMRI) analyses. Imprecise assertions may introduce the ecological fallacy as atlases are reflective of the constituent c...

Development and Validation of Novel Two-Stage Vascular Segmentation Model for Interventional Angiography

Authors: Abid Khan, Chad Klochko, Michael J Kovalchick, Hyeok Jun Lee, Hani Nasr, Krishnan Shyamkumar, Kundan S Thind

Affiliation: Henry Ford Radiology, Wayne State University, Henry Ford Health, HFHS

Abstract Preview: Purpose: Automated vascular segmentation in interventional angiography is challenged by contrast kinetics, vessel variations, and 2D projections, limiting the effectiveness of single-model approaches....

Dosimetric Comparison & Error Analysis of Aapm TG51 & WGTG51-e Protocol with Icru-90 Key-Data for High-Energy Clinical Electron Beam

Authors: Amar K. Basavatia, Sandeepan Ganguly, Lee C. Goddard, Wolfgang A. Tomé

Affiliation: Montefiore Medical Center

Abstract Preview: Purpose: To investigate the dosimetric impact of WGTG51-e Report 385, recently updated CoP for clinical electron beams. This study uses a chamber specific effective point of measurement (EPOM) shift t...

Enhanced Pelvic Organ Segmentation Using LLM-Driven Prompts for Prostate Cancer Low-Dose-Rate Brachytherapy

Authors: Yang Lei, Tian Liu, Ren-Dih Sheu, Meysam Tavakoli, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Emory University

Abstract Preview: Purpose:
The study aimed to improve target and organ at risk (OAR) segmentation in low-dose-rate brachytherapy (LDR-BT) for prostate cancer treatment, by integrating clinical guidelines into deep l...

Establishing a Protocol for Quality Assessment of Ultrasound Shear Wave Elastography (SWE) and Application to a Musculoskeletal (MSK) Task

Authors: Kevin M Brom, Jaydev K. Dave, Chunming Gu, Nicholas J. Hangiandreou, Zaiyang Long, Donald J Tradup

Affiliation: Mayo Clinic

Abstract Preview: Purpose: Ultrasound scanner onboard quality checks for shear wave elastography (SWE) rely on operator judgement and are insufficient. This study aims to establish a protocol for quality assessment and...

Expert Verification of AI-Generated Cardiac Substructures and Dosimetric Differences between Auto-Contoured and Manually Delineated Contours

Authors: Stephen R. Bowen, Richard Cheng, Kylie Kang, Janice Kim, Ana Paula Santos Lima, Dominic A. Maes, Juergen Meyer, Karen Ordovas, Kerry Reding

Affiliation: Department of Radiation Oncology, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiology, University of Washington, Division of Cardiology, University of Washington, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington

Abstract Preview: Purpose: Artificial intelligence (AI)-based auto-segmentation tools can increase the efficacy and reproducibility of radiotherapy (RT) treatment planning. This study evaluates the quality of AI-genera...

Fine-Tuning AI-Based Generative Models for Small-Sample Glioma MRI Generation.

Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...

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...

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...

Icrp Mesh-Type Reference Computational Phantoms Representing Pregnant Women and Fetuses

Authors: Wesley E. Bolch, Chansoo Choi, Chan Hyeong Kim, Suhyeon Kim, Bangho Shin, Yeon Soo Yeom

Affiliation: Hanyang University, University of Florida, 2) Department of Radiation Convergence Engineering, Yonsei University

Abstract Preview: Purpose: Task Group 103 of International Commission on Radiological Protection (ICRP) recently released new-generation adult and pediatric mesh-type reference computational phantoms (MRCPs) via ICRP P...

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 ...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

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

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

Investigate Deep-Learned MRI Reconstruction with Data Consistency Mechanism and Task-Informed Loss

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

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

Abstract Preview: Purpose: Ill-conditioned reconstruction problems in medical imaging, such as those arising from undersampled k-space data in MRI, can result in degraded image quality and clinical task-orientated perf...

Is Simplicity Even Better: Deep Learning Algorithms for Breath Motion Phase Prediction in Motion Management

Authors: Amanda J. Deisher, Andrew YK Foong, Witold Matysiak, Jing Qian, Xueyan Tang, Erik J. Tryggestad, Mi Zhou

Affiliation: Mayo Clinic

Abstract Preview: Purpose: Phase gating is commonly employed to mitigate the impact of tumor motion in radiotherapy. Due to the machine-specific time delay between triggering and radiation delivery, the triggering sign...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...

Knowledge-Based Three-Dimensional Dose Prediction for High Dose Rate Prostate Brachytherapy

Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi

Affiliation: UC San Diego, Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...

Large Language Model-Driven Agentic System for Collaborative Decision-Making in Radiotherapy Treatment Planning

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose:
This study aims to leverage large language model (LLMs) to develop a human-in-the-loop agentic framework, enhancing the efficiency of treatment planning in radiotherapy.
Methods:
A L...

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-Criteria Optimization in Medical Physics Resource Allocation: Design of an Efficient and Equitable Scheduling System

Authors: Dalton Griner, Kathryn L. Kolsky, Joseph John Lucido, Andrew J. Veres

Affiliation: Mayo Clinic

Abstract Preview: Purpose: This project aimed to automate a complex and time-consuming employee scheduling process. By replacing the traditional manual method with a multi-criteria optimization-based system (MCO), the ...

Multi-Scale, Multi-Task Framework with Jacobian Descent for Multi-Plan Dose Prediction in Sequential Boost Radiotherapy

Authors: Steve B. Jiang, Mu-Han Lin, Yu-Chen Lin, Austen Matthew Maniscalco, Dan Nguyen, David Sher, Xinran Zhong

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & 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, UT Dallas

Abstract Preview: Purpose:
Sequential boost radiotherapy (RT) poses a challenge in allocating dose across multiple plans while protecting organs at risk (OARs). Clinicians must decide whether OAR sparing should occu...

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...

Predicting Elective Pelvic Nodal Volumes with Deep Learning: A Tool to Facilitate Peer Review

Authors: Brian M. Anderson, Shiva K. Das, Meagan Foster, Anirudh Karunaker, Lawrence B. Marks, Lukasz Mazur, Michael Repka

Affiliation: UNC Chapel HIll, University of North Carolina at Chapel Hill, UNC School of Medicine, University of North Carolina

Abstract Preview: Purpose: Development of a peer review segmentation check system to identify deviations in physician contours of standard risk pelvic lymph nodes in patients receiving radiation therapy for prostate an...

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...

Re-Structuring of Clinical Education within a Therapy Medical Physics Residency Program

Authors: Kristofer K. Kainz, Eenas A. Omari, Eric S. Paulson

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: We present our therapy physics residency program’s revisions to its training structure, with the goals of more efficient clinical education and preservation of the residency’s clinical suppor...

Reinforcement Learning Based Machine Parameter Optimization for Two-Arc Prostate VMAT Planning

Authors: William T. Hrinivich, Junghoon Lee, Lina Mekki

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

Abstract Preview: Purpose: Volumetric modulated arc therapy (VMAT) planning is a computationally expensive process. In this work, we propose a reinforcement learning (RL) framework to automatically optimize dose rate a...

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 ...

Retrospective Analysis of Treatment Pauses Due to Intrafraction Movement for Frameless Single Fraction Gamma Knife Icon Radiosurgery

Authors: Nina Burbure, Tawfik G. Giaddui, Shidong Li, Curtis Miyamoto, Jeremy Price, Bin Wang

Affiliation: FCCC at Temple University Hospital

Abstract Preview: Purpose: Frameless gamma knife (GK) treatments use a thermoplastic mask coupled with high-definition motion management system that utilizes an infrared camera, and a reflective marker placed on the pa...

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 ...

Streamlined Stereotactic Radiosurgery (SRS) Commissioning Experience with a 6FFF Beam for an Elekta Versa: A Clinical Overview for Increased Precision.

Authors: Asma Amjad, Slade J. Klawikowski, Natalya V. Morrow, Haidy G. Nasief, Eric S. Paulson, An Tai, Hualiang Zhong

Affiliation: Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Accurate and precise linac-based SRS commissioning can be very challenging. Thus, it is important to increase the confidence in the measurement at each step prior to end-to-end testing. The p...

Task Specific Image Quality Assessment Using Spectral Photon-Counting CT.

Authors: Azza Mohamed Ahmed, Nadine Francis, Osama Khan, Nabil Maalej, Aamir Raja, Briya Tariq

Affiliation: Khalifa University

Abstract Preview: Purpose: The study aims to evaluate the task-specific diagnostic performance of spectral photon-counting CT (SPCCT) using application-specific phantoms.
Methods:
Parameters such as linearity res...

Task-Specific Deep-Neural-Network Architecture Optimization for CBCT Scatter Correction

Authors: Hoyeon Lee

Affiliation: University of Hong Kong

Abstract Preview: Purpose: Deep-learning approaches are widely investigated for Cone-Beam CT (CBCT) scatter correction to improve the quality of the linear-accelerator mounted CBCT. This study aims to optimize the deep...

Teaching an Old Dog New Tricks: Unlocking Hidden Potential in Existing Frameworks for Versatile Radiotherapy Applications

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:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...

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...

Unsupervised Task-Specific Histology Image Stain Standardization and Crypt Detection for Evaluating Normal Tissue Flash Irradiation Response

Authors: Muhammad Ramish Ashraf, Kerriann Casey, Suparna Dutt, Jie Fu, Edward Elliot Graves, Xuejun Gu, Hao Jiang, Brianna Caroline Lau, Billy W Loo, Weiguo Lu, Rakesh Manjappa, Stavros Melemenidis, Erinn Bruno Rankin, Lawrie Skinner, Luis Armando Soto, Murat Surucu, Vignesh Viswanathan, Zi Yang, Amy Shu-Jung Yu

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, 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, Department of Comparative Medicine, Stanford University School of Medicine, Department of Radiation Oncology, Stanford University Cancer Center

Abstract Preview: Purpose: The intestine is a classical preclinical model for studying radiation injury, and histological quantification of intestinal crypts is a key assay for assessing this response. However, substan...

Validating a Pre-Existing CT HU-to-Mass Density Curve for Direct Dose Calculation on High Quality Cbcts

Authors: Casey E. Bojechko, Tricia Chinnery, Grace Gwe-Ya Kim, Xenia Ray

Affiliation: University of California San Diego

Abstract Preview: Purpose: To evaluate the use of a calibration curve generated from the CT simulator for direct dose calculation on cone beam computed tomography (CBCT) images taken with the on-board imaging system. T...

Validation of an Open Source Automatic Segmentation Tool for Personalized Dosimetry

Authors: Klaus Bacher, Louise D'hondt, Jeff Rutten, Gwenny Verfaillie

Affiliation: Ghent University

Abstract Preview: Purpose: Manual organ segmentation is a very time-consuming but necessary process in personalized dosimetry. Automatic segmentation tools may alleviate this task. In this study the impact of automatic...