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Results for "improvement snr": 34 found

3D Image Quality Evaluation of a New CT Scanner Employing 3D Landmark Scans, Super Resolution Reconstruction, and Ag Beam Filtration

Authors: Ishika Bhaumik, John M. Boone, Michael T Corwin, Eric S Diaz, Ahmadreza Ghasemiesfe, Andrew M. Hernandez, Sarah E. McKenney, Misagh Piran, Ali Uneri, Eric L White

Affiliation: UC Davis, UC Davis Health, University of California, Johns Hopkins Univ

Abstract Preview: Purpose: A new model CT scanner (Canon Aquilion One Insight) was recently installed at our institution, and it included a 3D Landmark (3DLM) scan for automatic scan planning, a new deep learning recon...

A Comparative Study of Hypersight and Truebeam Cone Beam Computed Tomography Image Quality

Authors: Sorour Hosseini, YuHuei Jessica Huang, Thomas Boyd Martin, Geoffrey S. Nelson, Nicholas Pierre Nelson, Hui Zhao

Affiliation: University of Utah, Department of Radiation Oncology, Huntsman Cancer Institute, University of Utah

Abstract Preview: Purpose: To evaluate image quality—including noise, contrast-to-noise ratio (CNR), uniformity, and low-contrast visibility (LCV)—on the HyperSight and TrueBeam cone-beam computed tomography (CBCT) pla...

A No-Reference Medical Image Quality Assessment Method Based on Automated Distortion Recognition Technology: Application to Preprocessing in MRI-Guided Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Yuan Tang, Zilin Wang, Guohua Wu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
To develop a novel no-reference image quality assessment (NRIQA) method for evaluating the effectiveness of image preprocessing in MRI-guided radiotherapy (MRIgRT), thereby enhancing clini...

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...

Addressing Missing MRI Sequences: A DL-Based Region-Focused Multi-Sequence Framework for Synthetic Image Generation

Authors: Amir Abdollahi, Oliver Jäkel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome

Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH

Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...

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...

Assessment of the Quantum-CMOS Image Sensor for Use in Cherenkov Imaging during Radiation Therapy

Authors: Petr Bruza, Jeremy Eric Hallett, Brian W Pogue

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

Abstract Preview: Purpose: Cherenkov imaging is a powerful tool for localizing entrance and exit dose during radiotherapy treatment. The current implementation uses an intensified-CMOS (iCMOS) camera allowing for high-...

Augmenting Histopathology Lymphocyte Detection with Gpt-4 in-Context Visual Reasoning

Authors: Kyle J. Lafata, Casey Y. Lee, Xiang Li, Megan K. Russ, Zion Sheng

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose:
Traditional deep learning-based cell segmentation models face limitations, such as the need for extensive training data and retraining when encountering new cell types or domains. This stu...

Comparative Study between Sparse Primary Sampling Grid Scatter Correction and Low-Count Monte Carlo-Based Scatter Reduction with 3-D Richardson-Lucy Denoising

Authors: Alan Rui Li, Qihui Lyu, 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:
The Sparse Primary Sampling (SPS) grid was shown in a previous computational study to improve image quality by correcting scatter-induced effects and artifacts in Cone-beam Computed Tomogr...

Contrastive Learning and Hybrid CNN-Transformer Model for Unpaired MR Image Synthesis in Acute Cerebral Infarction

Authors: Kota Hirose, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami

Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University

Abstract Preview: Purpose: Synthesizing medical images can address the lack of or unscanned medical images, reducing scanner time and costs. However, paired image scarcity remains a challenge for image synthesis. We pr...

Cross-Slice Attention for Unsupervised 3D Pelvic CBCT to CT Translation

Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap

Affiliation: University of North Carolina at Chapel Hill, Huaqiao University

Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...

Denoising Diffusion-Weighted Images of Rectal Cancer Acquired on a 0.35 T Magnetic Resonance Imaging-Guided Linear Accelerator Using Singular Value Decomposition

Authors: Jacqueline M. Andreozzi, Tess Armstrong, Shiva Bhandari, John M Bryant, Jessica M Frakes, David J. Gladstone, Sarah E Hoffe, Kujtim Latifi, Arash Naghavi, Steven Nichols, Ibrahim M. Oraiqat, Russell Palm, Gage H. Redler, Stephen A Rosenberg, Joseph Weygand

Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Thayer School of Engineering, Dartmouth College, Department of Radiation Oncology, Ohio State University, Moffitt Cancer Center, Department of Radiation Oncology, Moffitt Cancer Center

Abstract Preview: Purpose: The MR-linac provides unique opportunities for integrating advanced imaging into radiotherapy workflows, but the lower sensitivity of systems like the 0.35T model can pose challenges for diff...

Development of an Orthogonal X-Ray Projections-Guided Cascading Volumetric Reconstruction and Tumor-Tracking Model for Adaptive Radiotherapy

Authors: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu

Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, 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: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...

Dosimetric Evaluation of Enhanced Dynamic Leaf Gap Modeling in Small-Field Clinical Plans: A Verification Study

Authors: Ian J. Butterwick, Sumudu Katugampola, ChangSeon Kim, Evan G. Meekins, Zhengdong Zhang

Affiliation: Mount Sinai Beth Israel, Gesinger Medical Center, Geisinger Medical Center

Abstract Preview: Purpose: To evaluate the dosimetric impact of enhanced dynamic leaf gap (EDLG) modeling in Eclipse V18.0 on small-field dosimetry within VMAT plans.
Methods: Plans with small fields (1 cm x 1 cm to...

Enhancing Synthetic Pelvic CT Images from CBCT Using Vision Transformer with Adaptive Fourier Neural Operators

Authors: Rashmi Bhaskara, Oluwaseyi Oderinde

Affiliation: Purdue University

Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...

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...

Evaluating the Impact of Reconstruction Algorithm on Wide-Angle Digital Breast Tomosynthesis System Optimization for Microcalcification Detection

Authors: Xiaoyu Duan, Xinyu Hu, Runqiu Li, Xiang Li

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

Abstract Preview: Purpose:
Accurate detection of small-sized microcalcifications (μCalcs) (< 500 µm) is critical for early breast cancer diagnosis, requiring optimal imaging systems and reconstruction algorithms. Ho...

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...

Explainable AI with Attention Gates for Transparent and Interpretable Lung Radiotherapy Plan Evaluation

Authors: Jeffrey D. Bradley, Steven J. Feigenberg, Cole Friedes, Yin Gao, Xun Jia, Kevin Teo, Lingshu Yin, Jennifer Wei Zou

Affiliation: Department of Radiation Oncology, University of Pennsylvania, Johns Hopkins University

Abstract Preview: Purpose: Understanding how physicians evaluate plans is critical for automatic planning and ensuring consistent, high-quality care. While deep-learning models excel in complex decision-making, the lac...

Feasibility Study of Deep Learning-Based MRI-to-PET Generation for Rectal Cancer: Overall Survival Prediction and Pathological Complete Response Assessment

Authors: Weigang Hu, Zhenhao Li, Jiazhou Wang, Xiaojie Yin, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aims to develop and validate a novel deep learning method to generate synthetic PET images for rectal cancer from MRI data. By incorporating metabolic information from the synth...

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,...

Generation of Virtual Lung PET Images from CT Data Via Deep Learning for Accelerated Tumor Detection and Preliminary Diagnosis

Authors: Pouya Azarbar, Nima Kasraie, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences

Abstract Preview: Purpose: Positron Emission Tomography (PET) is crucial for diagnosing and monitoring diseases due to its functional imaging capabilities. However, its high cost, significant radiation exposure, and li...

Image Quality Improvement Using a Patient-Specific Post-Trigger Delay Protocol for Coronary CT Angiography

Authors: Cecelia Brewington, Connor Edwards Miles All Leska-Kent, Kyrillos Grace, Katherine Hyde, Sabee Molloi, Shiva Mostafavi, Liqiang Ren, Alireza Shojazadeh, Justin Truong

Affiliation: Department of Radiology, UT Southwestern Medical Center, University of California, Irvine, University of Texas Southwestern

Abstract Preview: Purpose: To retrospectively assess image quality in coronary CT angiography (CCTA) using a patient-specific post-trigger delay (PTD) protocol, developed using half of the injection time plus a dispers...

Incorporating Cyclic Group Equivariance into Deep Learning for Reliable Reconstruction of Rotationally Symmetric Tomography Systems

Authors: Fang-Fang Yin, Lei Zhang, Yaogong Zhang

Affiliation: Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Rotational symmetry is an inherent property of many tomography systems (e.g., CT, PET, SPECT), arising from the circular arrangement or rotation of detectors. This study revisits the image re...

Modified Dehazenet for Scatter Correction in Triggered Imaging: Enhancing Visibility and Alignment Precision for Radiation Therapy

Authors: Hyosung Cho, Dae Yup Han, Duhee Jeon, Jiwon Park, Hyesun Yang

Affiliation: Department of Therapeutic Radiology, Yale University School of Medicine, Yonsei University

Abstract Preview: Purpose: Scatter in X-ray imaging degrades image quality, hindering the visibility of critical anatomical features and complicating patient alignment in radiation therapy. This study aims to improve s...

Monte Carlo Simulation of a Prototype Fluence Field Modulated Cone Beam CT System

Authors: Gregory J Bootsma, Tunok Mondol

Affiliation: University Health Network, Princess Margaret Cancer Center

Abstract Preview: Purpose:
To evaluate the impact of prototype fluence field modulation (FFM) cone-beam CT (CBCT) on dose reduction and image quality using Monte Carlo simulations. This study particularly looks at t...

Non-Planar Narrow-Beam CT: Near Scatter-Free, High-Resolution Breast Imaging at Screening Mammography Doses.

Authors: Peymon Ghazi

Affiliation: MALCOVA Inc.

Abstract Preview: Purpose: To develop a near scatter‐free breast CT imaging system that expands coverage of the posterior breast anatomy and enhances contrast resolution for solid masses and microcalcifications, while ...

Real Time Monte Carlo Dose Calculation for Clinical Cyberknife Radiation Therapy Based on Deep Learning Diffusion Model

Authors: Ruiyan Du, He Huang, Mingzhu Li, Ying Li, Hongyu Lin, Wei Liu, Shihuan Qin, Yiming Ren, Hui Xu, Lian Zhang, Xiao Zhang, Zunhao Zhang

Affiliation: Department of Radiation Oncology, Mayo Clinic, Medical AI Lab, The First Hospital of Hebei Medical University, Hebei Provincial Engineering Research Center for AI-Based Cancer Treatment Decision-Making, The First Hospital of Hebei Medical University, Department of Oncology, The First Hospital of Hebei Medical University

Abstract Preview: Purpose: Monte Carlo (MC) dose calculation is the gold standard in clinical CyberKnife radiation therapy (RT), considering its steep dose gradients and high-freedom non-coplanar beam angles, but extre...

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...

The Development of Large Field MR Guided Radiotherapy for Pelvic Lymph Node SBRT and Its Dosimetry Improvement

Authors: David Byun, Ting Chen, Paulina E. Galavis, Allison McCarthy, Hesheng Wang, Michael J Zelefsky

Affiliation: NYU Langone Health

Abstract Preview: Purpose: To summarize a MR guided adaptive workflow developed for pelvic lymph nodes (PLN) stereotactic radiotherapy using large field size on Elekta Unity© MR Linac system, and to quantitatively anal...

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...

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...

Validation of Updated CT-to-SPR Calibration Method with Icrp-145 Data for Carbon-Ion Radiotherapy

Authors: Min Cheol Han, Soorim Han, Chan Hyeong Kim, Jin Sung Kim, Seok-Ho Lee, Gahee Son, Yongdo Yun

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Hanyang University, Department of Integrative Medicine, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: The stoichiometric calibration method proposed by Kanematsu et al. (2016) has been widely adopted for CT number to stopping-power ratio (SPR) conversion in carbon-ion radiotherapy. With the r...