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Results for "noise levels": 40 found

23na Magnetic Resonance Imaging k-Space Denoising

Authors: Lorenzo Arsini, Andrea Ciardiello, Fabio Massimo D'Amore, Stefano Giagu, Federico Giove, Carlo Mancini-Terracciano, Cecilia Voena

Affiliation: Istituto Superiore di Sanità, Sapienza University of Rome, Università Sapienza Roma, Magnetic Resonance for Brain Investigation Laboratory, Museo Storico della Fisica e Centro di Studi e Ricerche Enrico Fermi

Abstract Preview: Purpose: To leverage newly developed heteronuclear magnetic resonance imaging (MRI) techniques, particularly sodium (23Na) imaging, for identifying potential biomarkers of Alzheimer's disease—such as ...

A Framework for the Standardization of Radiomics Classes in the Presence of Blur and Noise

Authors: Huay Din, Grace Jianan Gang, Grace Hyun Kim, Michael F. McNitt-Gray, Joseph W. Stayman, Yijie Yuan

Affiliation: Johns Hopkins University, John Hopkins University, University of Pennsylvania, David Geffen School of Medicine at UCLA

Abstract Preview: Purpose:
Radiomics rely on quantitative features to discern underlying biological signatures. However, feature dependence on the imaging systems themselves hampers the creation of reproducible and ...

A Novel Design of Photon-Counting Static Cone-Beam CT System for Dedicated Breast Imaging

Authors: Ahad Ollah Ezzati, Yile Fang, Xiaoyu Hu, Xun Jia, Kai Yang, Yuncheng Zhong

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Massachusetts General Hospital, Johns Hopkins University

Abstract Preview: Purpose: With breast cancer being one of the most prevalent cancers, regular screening is an effective strategy to mitigate the risk of malignancy. However, conventional energy-integrating detector (E...

A Simplified, Rigorous Procedure for Ultrasound Quality Assurance

Authors: Paul L. Carson, Sander Dekker, Stephen Z Pinter, Megan K. Russ

Affiliation: Clinical Imaging Physics Group, Department of Radiology, Duke University Health System, University of Michigan, Cablon Medical B.V., Univ of Michigan, Dept. of Radiology

Abstract Preview: Purpose:
To promote a simplified, inexpensive, but rigorous set of ultrasound QA tests and to evaluate their potential using a Randomly-placed very Hypoechoic Sphere Phantom (RHSP) in comparison to...

Adversarial Diffusion-Based Self-Supervised Learning for High-Resolution MR Imaging

Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Richard L.J. Qiu, Mojtaba Safari, Shansong Wang, Xiaofeng Yang, David Yu

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

Abstract Preview: Purpose: MRI offers excellent soft tissue contrast for diagnosis and treatment but suffers from long acquisition times, causing patient discomfort and motion artifacts. To accelerate MRI, supervised d...

An Automated System for MRI Coil Performance Evaluation

Authors: Michael Cuddy, Samuel J. Fahrenholtz, Khushnood Hamdani, Saman Jirjes, Robert G. Paden, Jeremiah W. Sanders, William F. Sensakovic, Wolfgang Stefan, Jeffrey Xiao, Yuxiang Zhou

Affiliation: Mayo, Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Title: An automated system for MRI coil performance evaluation

Purpose: To develop an automated quality control (QC) system for MRI coils to assess element-level signal-to-noise ratio (SNR), ar...

Analysis of Noise Power Spectra in MR Parallel Imaging

Authors: Sulaiman D. Aldoohan, Gerardo Garcia

Affiliation: University of Toledo Medical Center

Abstract Preview: Purpose: To evaluate the noise power spectra (NPS) of images acquired using parallel imaging with varying acceleration factors in 1-D and 3-D spaces and to compare the level of the power of the noise ...

Cherenkov Image Denoising with Diffusion-Based Deep-Learning for High-Fidelity Video Display of EBRT

Authors: Petr Bruza, Jeremy Eric Hallett, Brian W Pogue, Yucheng Tang, Shiru Wang

Affiliation: NVIDIA Corp, Dartmouth College, Thayer School of Engineering, Dartmouth College, University of Wisconsin-Madison, University of Wisconsin - Madison

Abstract Preview: Purpose: Cherenkov imaging allows for real-time visualization of megavoltage X-ray or electron beam delivery during radiation therapy. By using a time-gated intensified CMOS camera synchronized with a...

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 ...

Comparison of Ultra-High Resolution and Standard CT Imaging Modes for Small Vessel Visualization in Coronary CTA Using Photon Counting CT

Authors: Afrouz Ataei, Victor Moy, Mark P. Supanich

Affiliation: Rush University

Abstract Preview: Purpose: This study evaluates the impact of ultra-high resolution (UHR) mode on the visualization of small vessels in coronary computed tomography angiography (CTA) using a photon-counting CT scanner....

Contrast-Dependent Loss of Edge Sharpness in Low-Contrast Targets with Increasing Iterative Reconstruction Strength

Authors: Emi Ai Eastman, Christina Lee, Xinhua Li, Alexander W. Scott, Yifang (Jimmy) Zhou

Affiliation: Cedars-Sinai Medical Center

Abstract Preview: Purpose: Iterative reconstruction (IR) methods are valuable for reducing dose in modern CT; however, IR methods have the effect of reducing spatial resolution and hence the lesion edge sharpness. Furt...

Deep Learning-Based Denoising for Template Matching in Real-Time Tumor Tracking Using Kv Scattered X-Ray Imaging

Authors: Weikang Ai, Xiaoyu Hu, Xun Jia, Kai Yang, Yuncheng Zhong

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

Abstract Preview: Purpose: Real-time tumor tracking is critically important for respiratory motion management for lung cancer radiotherapy. A previously proposed application of a photon counting detector involves measu...

Detector Physics-Incorporated Diffusion Denoising Models for Digital Breast Tomosynthesis with Dual-Layer Flat Panel Detectors

Authors: Alexander Bookbinder, Matthew Tivnan, Xiangyi Wu, Wei Zhao

Affiliation: Stony Brook Medicine, Massachusetts General Hospital

Abstract Preview: Purpose: To investigate and benchmark a system-adaptive diffusion-based digital breast tomosynthesis (DBT) denoising model for a direct-indirect dual-layer flat panel detector (DI-DLFPD) with a k-edge...

Determine Noise Weighting Factor in Photon-Counting CT Via Deep Learning for Personalized Noise Reduction

Authors: Xinhui Duan, Roderick W. McColl, Mi-Ae Park, Liqiang Ren, Gary Xu, Kuan Zhang, Yue Zhang

Affiliation: UT Southwestern Medical Center, Department of Radiology, UT Southwestern Medical Center, Imaging Services, UT Southwestern Medical Center

Abstract Preview: Purpose:
Image-based deep-learning noise-reduction techniques have been developed for photon-counting CT (PCCT) to improve image quality with reduced radiation dose. The denoising strength is typic...

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 ...

Development of a Brain-like Digital Reference Object of Resting-State Functional MRI

Authors: Henry Szu-Meng Chen, Mu-Lan Jen, Vinodh A. Kumar, Ho-Ling Anthony Liu, Jian Ming Teo

Affiliation: School of Medicine, University of Colorado Denver, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Resting-state (rs-) fMRI detects functional networks by measuring synchronization of low-frequency oscillations in blood-oxygenation-level-dependent (BOLD) signals between brain regions. Stan...

Does the Method Matter? How in Hominum, In Vivo, in silico, and in Phantasma Measures Compare and Contrast Is Assessing the Utility of Photon Counting CT?

Authors: Ehsan Abadi, Njood Alsaihati, Steven T. Bache, Mridul Bhattarai, Cindy Marie McCabe, Francesco Ria, Ehsan Samei

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

Abstract Preview: Purpose: To compare and contrast alternative methods including reader (in hominum), phantom (in phantasma), in vivo, and in silico methods deployed to assess the performance of photon counting (PCCT) ...

Efficient Monte Carlo Proton Dose Calculation Using Denoising Diffusion Probabilistic Models

Authors: Chieh-Ya Chiu, Shen-Hao Li, Hsin-Hon Lin, Shu-Wei Wu

Affiliation: Department of Medical Imaging and Radiological Sciences, Chang Gung University, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital Linkou

Abstract Preview: Purpose: Monte Carlo simulation enables precise calculation of dose distribution in proton therapy through tracing the radiation particles with patient tissues. However, achieving clinical-level preci...

Emulating Human Perception of Low-Dose CT Image Quality Via Deep Generative Models

Authors: Jongduk Baek, Jooho Lee, Adam S. Wang

Affiliation: Stanford University, Yonsei University

Abstract Preview: Purpose: Optimizing the balance between radiation dose and image quality in computed tomography (CT) is important for minimizing patient X-ray exposure while maintaining diagnostic accuracy. While rad...

Enhancing T2-Weighted Brain MRI Resolution across Orientations Using AI-Based Volumetric Reconstruction

Authors: Mengqi Shen, Meghna Trivedi, Tony J.C. Wang, Andy (Yuanguang) Xu, Yading Yuan

Affiliation: Columbia University Medical Center, Dept of Med Hematology & Oncology, Data Science Institute at Columbia University, Columbia University Irving Medical Center, Department of Radiation Oncology, Columbia University Irving Medical Center

Abstract Preview: Purpose: T2-weighted (T2w) images are critical for identifying pathological changes due to their superior contrast in differentiating tissue types. However, they often lack detailed anatomical resolut...

Evaluating the Capabilities of Hypersight CBCT for Advanced Dual-Energy CBCT Imaging in Online Adaptive Radiotherapy

Authors: Yi-Fang Wang, Yading Yuan

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

Abstract Preview: Purpose: HyperSight, the latest CBCT technology from Varian Medical Systems, integrates rapid 6-second data acquisition with advanced iterative reconstruction and upgraded hardware. Previous studies h...

Evaluation of Noise and Dose Efficiency in Clinical Photon-Counting CT Colonography with Tin Prefiltration

Authors: Xinhui Duan, Vivek Nair, Liqiang Ren, KyuHo Song, Vasantha Vasan, Kuan Zhang, Yue Zhang

Affiliation: Department of Radiology, UT Southwestern Medical Center

Abstract Preview: Purpose: Minimizing radiation dose is crucial in CT colonography (CTC) screening and diagnosis. Tin (Sn) prefiltration is readily incorporated into clinical photon-counting CT (PCCT) scanners, yet its...

Feasibility of Efficient Offline Adaptive Replanning with Hypersight High-Performance Cone-Beam CT on Truebeam for Pelvis RT

Authors: Jochen Cammin, Shifeng Chen, Arun Gopal, Kai Huang, Jason K Molitoris, Amit Sawant, Kai Wang

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

Abstract Preview: Purpose: The HyperSight CBCT optional feature on Varian TrueBeam linacs offers a larger field-of-view, improved Hounsfield units (HU) accuracy, and overall improved image quality, including metal arti...

From Noisy Signals to Accurate Maps: Transforming Look-Locker MRI with an Intelligent T₁ Estimation

Authors: Prabhu C. Acharya, Hassan Bagher-Ebadian, Stephen L. Brown, James R. Ewing, Mohammad M. Ghassemi, Benjamin Movsas, Farzan Siddiqui, Kundan S Thind

Affiliation: Michigan State University, Oakland University, Henry Ford Health

Abstract Preview: Purpose: Accurate T1 quantification using T One by Multiple Read Out Pulse (TOMROP) sequences is essential for physiological assessments in dynamic-contrast-enhanced (DCE) MRI and T1 mapping studies. ...

Impact of Computed Tomography Noise Reference Levels in a Pediatric Hospital

Authors: Samuel L. Brady, Joseph G. Meier

Affiliation: Cincinnati Childrens Hospital Med Ctr

Abstract Preview: Purpose:
To establish noise reference levels for our pediatric hospital.
Methods:
Water equivalent diameter (Dw) and image noise was automatically measured by using a global noise algorithm i...

Improved SNR and Estimation Accuracy for Deuterium-MRI Acquired with Chemical Shift Imaging at 7 Tesla

Authors: Muhammed AR Anjum, Andrew J. Fagan

Affiliation: Mayo Clinic

Abstract Preview: Purpose:
This study describes a novel post-processing method to boost image SNR for deuterium-MRI acquired using chemical shift imaging (CSI) at 7T. Deuterium MRI via exogenous administration of a ...

In silico Evaluation Vs Standard Phantom Evaluation of a Deep Learning Reconstruction Algorithm

Authors: Naruomi Akino, Kirsten Lee Boedeker, Ilmar Hein, Dylan Mather, Akira Nishikori, Daniel W Shin

Affiliation: Canon Medical Systems Corporation, Canon Medical Research USA

Abstract Preview: Purpose: To validate the performance a deep learning reconstruction (DLR) algorithm in an anatomical background compared to a uniform phantom background.
Methods: An analytic forward projection mod...

Initial Phantom Studies Towards Implementation of Sequential Dual Energy CBCT on an Adaptive Radiotherapy Linac Platform

Authors: James M. Balter, Alexander Moncion, Ikechi S Ozoemelam

Affiliation: University of Michigan

Abstract Preview: Purpose: Sequential dual-energy cone beam computed tomography (DE-CBCT) integrated with an online adaptive platform could potentially improve soft tissue visualization for more accurate anatomical del...

Inverse Geometry Photon Counting CBCT

Authors: Saree Alnaghy, Owen Thomas Dillon, Sean P Hood, Paul J. Keall, Ricky O'Brien, Tess Reynolds

Affiliation: Image X Institute, Faculty of Medicine and Health, The University of Sydney, University of Wollongong, Medical Radiations, School of Health and Biomedical Sciences, RMIT University

Abstract Preview: Purpose: Photon Counting Detectors (PCDs) have been demonstrated to improve resolution, contrast and lesion detectability in fan-beam CT. There is naturally a desire to bring these improvements to Con...

Lung Nodule Volume Estimation: Performance of Conventional Energy-Integrating and Cdznte-Photon-Counting CT Using Hybrid Reconstruction Method

Authors: Gisell Ruiz Boiset, Paulo ROBERTO Costa, Luuk J Oostveen, Elsa Bifano Pimenta, Ioannis Sechopoulos, Alessandra Tomal

Affiliation: Radboud University Medical Center, University of São Paulo (USP), Institute of Physics, Universidade Estadual de Campinas. Instituto de Física Gleb Wataghin

Abstract Preview: Purpose: The study evaluated the accuracy and precision of lung nodule volume measurements, specifically solid nodules (SNs) and ground-glass opacities (GGOs) in different imaging settings.
Methods...

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...

Routine Quality Monitoring in Abdominal CT Using Global Noise Reference Levels in a 4-Parameter Protocol Summary Plot

Authors: Joke Binst, Hilde TC Bosmans, Niki Fitousi, Bram Miseur, Dimitar Petrov, Kwinten Torfs, Janne Vignero

Affiliation: Qaelum NV, Department of radiology, UZLeuven, Department of imaging and pathology, KULeuven

Abstract Preview: Purpose: Routine quality monitoring in CT abdomen is crucial for ensuring optimal image quality and patient safety, but the simultaneous evaluation of all aspects of importance is challenging. The pur...

Synthetic Spheres: Ultrasound Image Quality Assessment with a Uniform Phantom

Authors: Ted Lynch

Affiliation: Sun Nuclear, a Mirion Medical Company

Abstract Preview: Purpose: A novel ultrasound quality assurance method is presented that constructs “synthetic spheres” at arbitrary locations within the image frame by combining correlation length measurements from a ...

Synthetic Vs. Conventional Planar Imaging: Performance and Clinical Feasibility

Authors: Jennifer Kwak, Chelsea Manica, Justin K. Mikell, Michael Silosky, Wendy Siman

Affiliation: Washington University School of Medicine in St. Louis, University of Colorado Anschutz Medical Campus, School of Medicine, Rocky Vista University

Abstract Preview: Purpose:
This study evaluates synthetic planar imaging (synP) from SPECT projections against conventional planar imaging, focusing on detectability, spatial resolution, and feasibility. SynP allows...

Tin-Filtered Spectral Shaping Technique in Clinical Photon-Counting CT: Impact on Noise Magnitude By Object Size, Radiation Dose, and Spectral Reconstruction Type

Authors: Xinhui Duan, Vivek Nair, Liqiang Ren, KyuHo Song, Kuan Zhang, Yue Zhang

Affiliation: Department of Radiology, UT Southwestern Medical Center

Abstract Preview: Purpose: To evaluate how tin-filtered spectral shaping in clinical photon-counting computed tomography (PCCT) affects noise magnitude across varying object sizes, radiation doses, and spectral reconst...

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 Multi-Peak Reconstructions for Dosimetry of Fast and Quantitative Lutetium-177 SPECT/CT

Authors: Julia Brosch-Lenz, Munir Ghesani, Francesc Massanes, Michael Morris, Babak Saboury, Eliot Siegel, Alexander Hans Vija

Affiliation: Institute of Nuclear Medicine, Siemens Medical Solutions USA Inc., Molecular Imaging

Abstract Preview: Purpose: Quantitative imaging of the radiopharmaceutical distribution is crucial for treatment evaluation and dosimetry. However, as patient numbers for Lutetium-177-(177Lu)-labelled therapies continu...

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...

Validation of a Simulation Tool and in-Silico Assessment of Low Contrast Detectability for Super-Resolution Deep Learning Reconstruction

Authors: Naruomi Akino, Kirsten Lee Boedeker, Ilmar Hein, Akira Nishikori, Daniel W Shin

Affiliation: Canon Medical Systems Corporation, Canon Medical Research USA

Abstract Preview: Purpose: To validate a simulation tool using physics-based image quality metrics in both phantom and patient data, and to assess the low contrast detectability (LCD) of Super Resolution-Deep Learning ...

Virtual Monoenergetic Imaging for Radiotherapy: A Single CT Acquisition for Both Target Delineation and Dose Calculation

Authors: Harold Y Hu, Yanle Hu, Shuai Leng, Maryam Sadeghian, Joe Swicklik

Affiliation: Mayo Clinic Arizona, Basis Scottsdale, Mayo Clinic

Abstract Preview: Purpose: Radiotherapy CT simulation often requires two scans: a non-contrast scan for dose calculation and a contrast-enhanced scan for target delineation. Photon-counting-detector (PCD) CT allows the...