Search Submissions 🔎

Results for "organ noise": 18 found

12 Year Clinical Experience with Low-Tesla MRI for Tumor Progression

Authors: Soon N. Huh, Perry B. Johnson, Jiyeon Park, Ryan Stevens

Affiliation: University of Florida Health Proton Therapy Institute, UF Health Proton Therapy Institute, UFHPTI

Abstract Preview: Purpose:
Low-Tesla MRI (0.23T Panorama MR Scanner, Philips) has been used for tumor progression during proton therapy treatments, and for initial contouring in addition to diagnostic MRI. The pulse...

AI-Based Registration-Free 3T T2-Weighted MRI Synthesis Using Truefisp MRI Acquired on a 0.35T MR-Linac System

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Cynthia Fu-Yu Chuang, Yu Gao, Dimitre Hristov, Lianli Liu, Lawrie Skinner, Lei Xing

Affiliation: Department of Radiation Oncology, Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
MR-guided radiation therapy has introduced a significant leap in cancer treatment by allowing adaptive treatment. The low-field MR-guided system predominantly uses the TrueFISP sequence, w...

An Open-Access Toolkit to Generate Realistic CT and Low-Field MR Images Based on an Xcat Phantom

Authors: Debora de Souza Antonio, Romy Guthier, Konrad Pawel Nesteruk, Erno Sajo, William Paul Segars, Gregory C. Sharp, Atchar Sudhyadhom, Hengyong Yu

Affiliation: Massachusetts General Hospital, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School,, Massachusetts General Hospital and Harvard Medical School, University of Massachusetts Lowell

Abstract Preview: Purpose: To develop an open-access toolkit for rapidly generating simultaneously realistic CT scans and low-field MR images of the abdominal region, based on patient data, while employing an XCAT phan...

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...

Comprehensive Evaluation of High-Performance Cone-Beam Computed Tomography on C-Arm and Ring-Gantry Linacs for Adaptive Radiation Therapy

Authors: Laura I. Cervino, Karen Episcopia, Hsiang-Chi Kuo, Sangkyu Lee, Seng Boh Gary Lim, Shih-Chi Lin, Grace Tang

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

Abstract Preview: Purpose: This study evaluated the performance of the HyperSight Cone-Beam Computed Tomography (CBCT) system on a TrueBeam C-arm LINAC (TB) and two Ethos ring-gantry LINACs (ES) for adaptive radiation ...

Deep-Dive Comparative Assessment between Digitally Reconstructed Radiographs and X-Ray Digital Radiographs from Lung CT Scans

Authors: Xinyi Fu, Dan Ruan, Ke Sheng

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

Abstract Preview: Purpose:
Digitally reconstructed radiographs (DRRs) are easy to generate and widely used to establish research protocols in pulmonary diagnosis and image-guided radiotherapy tasks. A question remai...

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 Radiation Oncology Imaging with a Novel Variational Model Decomposition, Radon Transformation, and Kohonen Self-Organizing Map Denoising Framework

Authors: Hassan Bagher-Ebadian, Justine M. Cunningham, Anthony J. Doemer, Mohammad M. Ghassemi, Joshua P. Kim, Benjamin Movsas, Kundan S Thind

Affiliation: Michigan State University, Henry Ford Health

Abstract Preview: Purpose: Reduction of noise in medical images critically enables improved accuracy in delineating tumors and organs at risk, leading to more precise treatment planning and safer image-guided radiation...

Four-Dimensional on-Beam Computed Tomography Reconstruction from Projection Image Differences Representing Motion Change

Authors: Kwang-Ho Cheong, Seungryong Cho, Joonil Hwang, Jae Won Jung, Hoyeon Lee, Raymond Hyunwoo Moon, Inhwan Yeo, Jihyung Yoon

Affiliation: East Carolina University, INOVA Schar Cancer Institute, University of Hong Kong, Hanllym University, KAIST, University of Rochester

Abstract Preview: Purpose: Monitoring a target and neighboring organs during beam delivery is crucial for successful radiotherapy (RT). Conventional transit imaging methods lack volumetric reconstruction capabilities, ...

Generalizable 7T T1 Map Synthesis from 1.5T and 3T T1W MRI for High-Resolution MRI-Guided Radiation Therapy

Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Hui Mao, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu

Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, Emory University School of Medicine

Abstract Preview: Purpose: MRI-guided radiation therapy (MRgRT) benefits significantly from enhanced soft-tissue contrast and spatial resolution, which aid in accurately delineating tumors and organs at risk. Although ...

Hyperpolarized 13c Image Superresolution with Deep Learning

Authors: Kofi M. Deh, Tamas Jozsa, Tsang-Wei Tu

Affiliation: Cranfield University, Howard University Hospital, Howard University

Abstract Preview: Purpose: To enhance the quality of hyperpolarized (HP) 13C magnetic resonance images by integrating deep learning with perfusion modeling.
Methods: A convolutional neural network (CNN) and a superr...

Multicentric Characterization of Organ-Based Tube Current Modulation in Thoracic and Abdominopelvic Computed Tomography: A Dosimetric and Image Quality Study

Authors: Corentin Desport, Dominique Iacchetti, Nicolas Kien, Ramiro Moreno, Melodie Munier, Séléna Pondard

Affiliation: Fibermetrix, Alara Expertise, Alara Group

Abstract Preview: Purpose: To evaluate the efficiency of organ-based tube current modulation (OBTCM) in thoracic and abdominopelvic Computed Tomography (CT) for different radiology departments and manufacturers. This s...

Noise Sensitivity of Benchmark Whole-Body CT Segmentation Models: Totalsegmentator and Vista3D Performance on an Independent Dataset

Authors: Samuel L. Brady, Shruti Hegde, Alexander Knapp, Usman Mahmood, Joseph G. Meier, Elanchezhian Somasundaram, Zachary Taylor

Affiliation: Cincinnati Children's Hospital Medical Ctr, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Cincinnati Children's Hospital Medical Center, Cincinnati Childrens Hospital Med Ctr

Abstract Preview: Purpose:
To assess how two benchmark multi-organ CT segmentation models respond to varying image noise levels.
Methods:
This study utilized the pediatric CT dataset from The Cancer Imaging Ar...

Optimization of the U-Net Model for the Radiation Dose Prediction in Lung Cancer RT Plans and Its Uncertainty Quantification

Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...

Simulating Realistic Digital Phantoms for Virtual Clinical Trials in Radiology and Radiation Oncology Using a Deep-Learning Based Conditional Denoising Diffusion Probabilistic Model (c-DDPM)

Authors: Matthew Brown, Yushi Chang, Jinhyuk Choi, William Silva Mendes, Lei Ren, Aman Sangal, William Paul Segars, Phuoc Tran, Hualiang Zhong

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Digital phantoms like XCAT are essential for imaging and treatment optimization in radiology and radiation oncology. However, the lack of realistic textures (HU distribution) in XCAT limits i...

Structure-Based Diffusion Model for CT Synthesis from MR Images for Radiotherapy Treatment Planning

Authors: Samuel Kadoury, Redha Touati

Affiliation: Polytechnique Montréal

Abstract Preview: Purpose:
Generating synthetic CT images from MR acquisitions for radiotherapy planning allows to integrate soft tissue contrast alongside density information stemming from CT, thus improving tumor ...

The Feasibility of Ethos-Based Pulsed Reduced Dose-Rate (PRDR) Radiotherapy

Authors: Chia-Lung Chien, Renteng Hou, Wen C. Hsi, Faraz Kalantari, Ganesh Narayanasamy, Zhong Su

Affiliation: University of Arkansas for Medical Sciences, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)

Abstract Preview: Purpose:
PRDR is an effective re-irradiation treatment for patients who have already reached the tolerance dose to their organs at risk (OARs). While PRDR is implemented on TrueBeam by limiting the...

Voxel-Based Micro-Yucatan Minipig Phantoms for Use in Internal Dosimetry

Authors: John P. Aris, Wesley E. Bolch, Natalia Estefania Carrasco-Rojas, Ann M. Chan, Chansoo Choi, Aitor Gallastegui Menoyo, Rowan James Milner, Bangho Shin, Maria M. Von Chamier

Affiliation: University of Florida

Abstract Preview: Purpose: In preclinical studies, minipigs serve as valuable experimental models for predicting absorbed doses due to their anatomical and physiological similarities to humans. However, minipig computa...