Explanipedia

Integrating Artificial Intelligence into Language Pedagogy: A Step-by-Step Tutorial for Creating Question-Making Games Open

Bruno De Man, Chong Peng Hwa, Choo Kim Fong, Toh Ling Ling · 2025

This article presents a practical tutorial for language instructors, intending to explore the integration of artificial intelligence (AI) into teaching and the enhancement of classroom effectiveness through the design of interactive questi…

AAPM CT metal artifact reduction grand challenge Open

Eri Haneda, Nils Peters, Jiayong Zhang, Grigorios Marios Karageorgos, Wenjun Xia , et al. · 2025

Background Metal artifact reduction (MAR) is a long‐standing challenge in CT imaging. The presence of highly attenuating objects, such as dental fillings, hip prostheses, spinal screws/rods, and gold fiducial markers, can introduce severe …

Simulating and correcting the pileup effect in deep‐silicon photon‐counting CT Open

Erik Fredenberg, D. Collin, Louis Carbonne, Mingye Wu, Bruno De Man , et al. · 2025

Background Photon‐counting computed tomography (CT) bears promise to substantially improve spectral and spatial resolution. One reason for the relatively slow evolution of photon‐counting detectors in CT—the technology has been used in nuc…

Bolus tracking from pulsed x‐ray projections: A feasibility study using a five‐dimensional cardiac CT contrast dynamics model Open

Eri Haneda, Ivo G.H. Jansen, Pengwei Wu, Jed D. Pack, Albert Hsiao , et al. · 2024

Background Cardiac computed tomography (CT) exams are some of the most complex CT exams due to the need to carefully time the scan when the heart chambers are near the peak contrast concentration. With current “bolus tracking” and “timing …

Coronary atherosclerotic plaque characterization with silicon‐based photon‐counting computed tomography (CT): A simulation‐based feasibility study Open

Mengzhou Li, Mingye Wu, Jed D. Pack, Pengwei Wu, Pingkun Yan , et al. · 2024

Background Recent photon‐counting computed tomography (PCCT) development brings great opportunities for plaque characterization with much‐improved spatial resolution and spectral imaging capability. While existing coronary plaque PCCT imag…

CT-based Anomaly Detection of Liver Tumors Using Generative Diffusion Prior Open

Yongyi Shi, Chuang Niu, Amber L. Simpson, Bruno De Man, Richard Kinh Gian , et al. · 2024

CT is a main modality for imaging liver diseases, valuable in detecting and localizing liver tumors. Traditional anomaly detection methods analyze reconstructed images to identify pathological structures. However, these methods may produce…

A Denoising Diffusion Probabilistic Model for Metal Artifact Reduction in CT Open

Grigorios M. Karageorgos, Jiayong Zhang, Nils Peters, Wenjun Xia, Chuang Niu , et al. · 2024

The presence of metal objects leads to corrupted CT projection measurements, resulting in metal artifacts in the reconstructed CT images. AI promises to offer improved solutions to estimate missing sinogram data for metal artifact reductio…

Simulated deep CT characterization of liver metastases with high-resolution filtered back projection reconstruction Open

Christopher Wiedeman, Peter W. Lorraine, Ge Wang, Richard Kinh Gian, Amber L. Simpson , et al. · 2024

Early diagnosis and accurate prognosis of colorectal cancer is critical for determining optimal treatment plans and maximizing patient outcomes, especially as the disease progresses into liver metastases. Computed tomography (CT) is a fron…

Photon-counting CT using a Conditional Diffusion Model for Super-resolution and Texture-preservation Open

Christopher Wiedeman, Chuang Niu, Mengzhou Li, Bruno De Man, Jonathan S. Maltz , et al. · 2024

Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing. Deep learning is a possible method for super-resolution (SR), but sourcing paired trainin…

Development and tuning of models for accurate simulation of CT spatial resolution using CatSim Open

Jiayong Zhang, Mingye Wu, Paul B. Fitzgerald, Stephen Araujo, Bruno De Man · 2024

Objective . We sought to systematically evaluate CatSim’s ability to accurately simulate the spatial resolution produced by a typical 64-detector-row clinical CT scanner in the projection and image domains, over the range of clinically use…

A coronary artery phantom for task-based CT performance assessment and a comparative study of clinical CT, photon counting CT, and micro CT Open

Jed D. Pack, Paul B. Fitzgerald, Stephen Araujo, Ying Fan, Grant M. Stevens , et al. · 2024

While drastic improvements in CT technology have occurred in the past 25 years, spatial resolution is one area where progress has been limited until recently. New photon counting CT systems, are capable of much better spatial resolution th…

Coronary Atherosclerotic Plaque Characterization with Photon-counting CT: a Simulation-based Feasibility Study Open

Mengzhou Li, Mingye Wu, Jed D. Pack, Pengwei Wu, Bruno De Man , et al. · 2023

Recent development of photon-counting CT (PCCT) brings great opportunities for plaque characterization with much-improved spatial resolution and spectral imaging capability. While existing coronary plaque PCCT imaging results are based on …

Deep learning tomographic reconstruction through hierarchical decomposition of domain transforms Open

Lin Fu, Bruno De Man · 2022

Cardiac CT blooming artifacts: clinical significance, root causes and potential solutions Open

Jed D. Pack, Mufeng Xu, Ge Wang, Lohendran Baskaran, James K. Min , et al. · 2022

This review paper aims to summarize cardiac CT blooming artifacts, how they present clinically and what their root causes and potential solutions are. A literature survey was performed covering any publications with a specific interest in …

A five-dimensional cardiac CT model for generating virtual CT projections for user-defined bolus dynamics and ECG profiles Open

Eri Haneda, Bernhard E. H. Claus, Jed D. Pack, Darin Okerlund, Albert Hsiao , et al. · 2022

Cardiac CT exams are some of the most complex CT exams due to need to carefully time the scan to capture the heart during the quiescent cardiac phase and when the contrast bolus is at its peak concentration. We are interested in developing…

Estimation of contrast agent concentration from pulsed-mode projections to time contrast-enhanced CT scans Open

Isabelle Heukensfeldt Jansen, Eri Haneda, Bernhard E. H. Claus, Jed D. Pack, Albert Hsiao , et al. · 2022

Cardiac CT exams are some of the most complex CT exams due to the need to carefully time the scan to capture the heart during a quiescent cardiac phase and when the intravenous contrast bolus is at its peak concentration in the left and/or…

A virtual imaging trial framework to study cardiac CT blooming artifacts Open

Ying Fan, Jed D. Pack, Bruno De Man · 2022

Cardiac CT is a safe, accurate, non-invasive method widely employed for diagnosis of coronary artery disease (CAD) and planning therapeutic interventions. Even with state-of-the-art CT technology, calcium blooming artifacts may limit the a…

XCIST—an open access x-ray/CT simulation toolkit Open

Mingye Wu, Paul B. Fitzgerald, Jiayong Zhang, W. Paul Segars, Hengyong Yu , et al. · 2022

Objective . X-ray-based imaging modalities including mammography and computed tomography (CT) are widely used in cancer screening, diagnosis, staging, treatment planning, and therapy response monitoring. Over the past few decades, improvem…

Projection decomposition via univariate optimization for dual-energy CT Open

Wenxiang Cong, Bruno De Man, Ge Wang · 2022

Dual-energy computed tomography (DECT) acquires two x-ray projection datasets with different x-ray energy spectra, performs material-specific image reconstruction based on the energy-dependent non-linear integral model, and provides more a…

Monochromatic image reconstruction via machine learning Open

Wenxiang Cong, Yan Xi, Bruno De Man, Ge Wang · 2021

X-ray computed tomography (CT) is a nondestructive imaging technique to reconstruct cross-sectional images of an object using x-ray measurements taken from different view angles for medical diagnosis, therapeutic planning, security screeni…

Semiempirical, parameterized spectrum estimation for x‐ray computed tomography Open

Paul B. Fitzgerald, Stephen Araujo, Mingye Wu, Bruno De Man · 2021

Purpose To develop a tool to produce accurate, well‐validated x‐ray spectra for standalone use or for use in an open‐access x‐ray/CT simulation tool. Spectrum models will be developed for tube voltages in the range of 80 kVp through 140 kV…

Virtual Monoenergetic CT Imaging via Deep Learning Open

Wenxiang Cong, Yan Xi, Paul B. Fitzgerald, Bruno De Man, Ge Wang · 2020

X-ray Monochromatic Imaging from Single-spectrum CT via Machine Learning Open

Wenxiang Cong, Bruno De Man, Ge Wang · 2020

In clinical CT system, the x-ray tube emits polychromatic x-rays, and the x-ray detectors operate in the current-integrating mode. This physical process is accurately described by an energy-dependent non-linear integral equation. However, …

A new series expansion method and its application to photon-counting CT reconstruction Open

Mats Persson, Lin Fu, Peter M. Edic, Bruno De Man · 2020

The introduction of photon-counting detectors in x-ray computed tomography raises the question of how reconstructionalgorithms should be adapted to photon-counting measurement data. The transition from energyintegratingto photon-counting d…

A hierarchical approach to deep learning and its application to tomographic reconstruction Open

Lin Fu, Bruno De Man · 2019

Deep learning (DL) has shown unprecedented performance for many image analysis and image enhancement tasks. Yet, solving large-scale inverse problems like tomographic reconstruction remains challenging for DL. These problems involve non-lo…

Model‐based dose reconstruction for <span>CT</span> dose estimation Open

Mingye Wu, Zhye Yin, Bruno De Man · 2017

Purpose Our goal is to develop a model‐based approach for CT dose estimation. We previously presented a CT dose estimation method that offered good accuracy in soft tissue regions but lower accuracy in bone regions. In this work, we propos…

Dual-Energy Computed Tomography Open

Reza Forghani, Bruno De Man, Rajiv Gupta · 2017

There are increasing applications of dual-energy computed tomography (CT), a type of spectral CT, in neuroradiology and head and neck imaging. In this 2-part review, the fundamental principles underlying spectral CT scanning and the major …

Dual-Energy Computed Tomography Open

Reza Forghani, Bruno De Man, Rajiv Gupta · 2017

There are increasing applications and use of spectral computed tomography or dual-energy computed tomography (DECT) in neuroradiology and head and neck imaging in routine clinical practice. Part 1 of this 2-part review covered fundamental …

Quest for the ultimate cardiac CT scanner Open

Paul B. Fitzgerald, Peter M. Edic, Hewei Gao, Yannan Jin, Jiao Wang , et al. · 2017

Purpose To quantitatively evaluate and compare six proposed system architectures for cardiac CT scanning. Methods Starting from the clinical requirements for cardiac CT, we defined six dedicated cardiac CT architectures. We selected these …

Model and reconstruction of a K-edge contrast agent distribution with an X-ray photon-counting detector Open

Bo Meng, Wenxiang Cong, Yan Xi, Bruno De Man, Jian Yang , et al. · 2017

Contrast-enhanced computed tomography (CECT) helps enhance the visibility for tumor imaging. When a high-Z contrast agent interacts with X-rays across its K-edge, X-ray photoelectric absorption would experience a sudden increment, resultin…

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