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Results for "noise variability": 12 found

A Comparative Evaluation of CT Global Noise Calculation Methods for Upcoming CMS Image Quality Measure

Authors: Gary Y. Ge, Charles Mike Weaver, Jie Zhang

Affiliation: University of Kentucky

Abstract Preview: Purpose: The recently introduced CMS regulation on CT dose and image quality mandates the use of global noise as the metric for image quality assessment. The regulation cites two methods for calculati...

A Vqvae-Based Framework with Embedded Kullback-Leibler Divergence for Stochastic and Diverse Dose Prediction

Authors: Weigang Hu

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose: The purpose of this study is to introduce a VQVAE-based framework that addresses the limitations of conventional dose prediction methods, which rely on fixed deep learning models that produce...

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...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity

Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...

Evaluating 177Lu-PSMA-I&t Reconstruction Parameter Influences on Image Quality and Quantification

Authors: Martin Auerbach, Jeremie Calais, Johannes Czernin, Magnus Dahlbom, Zachary Ells, Adrien Holzgreve, Koichiro Kimura, Karam Masri, Catherine (Caffi) Meyer, David Sennung

Affiliation: Department of Nuclear Medicine, UCLA, UCLA, University of California, Los Angeles

Abstract Preview: Purpose: Lutetium-177 PSMA SPECT/CT imaging offers the possibility of qualitative image analysis for tumor response assessment and quantitative image analysis for individualized dosimetry. However, th...

Inconsistencies in Methods for CMS Size-Adjusted Dose Measure

Authors: Alexander Alsalihi, Gary Y. Ge, Charles Mike Weaver, Jie Zhang

Affiliation: University of Kentucky

Abstract Preview: Purpose: The upcoming CMS regulation, titled “Excessive Radiation Dose or Inadequate Image Quality for Diagnostic Computed Tomography (CT) in Adults”, employs two measures, size-adjusted DLP (SAD) and...

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...

Performance Evaluation of CT-Based Lung Tumor Classification Deep Learning Algorithms Under Centralized and Federated Learning Frameworks

Authors: Yifei Hao, Chengliang Jin, Wenxuan Li, Bing Luo, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Ruojun Zhou

Affiliation: School of Future Science and Engineering, Soochow University, Electrical and Computer Engineering Graduate Program, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Federated learning is a patient privacy-protecting technique that has recently been applied in the medical field. This study aims to evaluate the performance of several deep learning networks...

Respiratory Monitoring in Human Subjects Using a Low-Cost Optical Imaging System Prototype

Authors: Marian Axente, Mandeep Kaur

Affiliation: Emory University

Abstract Preview: Purpose: To validate a low-cost optical imaging system for respiratory monitoring by comparing its accuracy and feasibility against the clinical gold standard in human subjects.
Methods: Following ...

Sources of Variability in Evaluating Ultrasound Imaging Performance Using Randomly-Distributed Hypoechoic Sphere Phantom

Authors: Cristel Baiu, Zheng Feng Lu, Dufan Wu, Baihui Yu

Affiliation: University of Wisconsin, Massachusetts General Hospital, University of Chicago

Abstract Preview: Purpose: IEC TS 62791:2022 specified a clinically meaningful and quantitative framework for evaluating diagnostic ultrasound performance by measuring the lesion signal-to-noise ratio (LSNR) using rand...

Toward Harmonized AI-Based Quantitative CT: A Voxel-Printed, Patient Specific Phantom for Cross-Platform Harmonization

Authors: Aditya P. Apte, Joseph O. Deasy, Yusuf Emre Erdi, Anqi Fu, Johannes Hertrich, Andrew Jackson, Usman Mahmood, Jason Ocana, Trahan Sean, Amita Shukla-Dave

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

Abstract Preview: Purpose: Automated AI-based quantitative CT tools hold immense promise for advancing clinical decision-making, yet their reproducibility and generalizability remain vulnerable to variability in imagin...

Transforming CT Technologist Training: Real-Time Feedback, Gamification, and Phantom-Based Education for Accurate Patient Positioning

Authors: Rebecca Lamoureux, Zahra (Zara) Razi, Zachary Whipps

Affiliation: University of New Mexico Hospital

Abstract Preview: Purpose: Patient mispositioning in CT imaging contributes to inconsistent radiation dose delivery and suboptimal image quality, impacting patient safety and diagnostic outcomes. This study evaluates a...