13 citations · 46 across the 20 of their papers we have counts for
21 papers
Efficient Noise Context-Aware Representation for Low-Dose CT Denoising
Minwoo Yu, N. Robert Bennett, Jongduk Baek +1
While deep learning-based denoising has become widely adopted in low-dose CT, conventional models use generic architectures designed for natural images, failing to account for non-…
Evaluation of Silicon-Based Photon-Counting CT for Coronary Stenosis Quantification with Realistic Coronary Artery Phantoms
Maria Jose Medrano, Jed Pack, Stephen Araujo +5
Objective: To quantify the impact of high-resolution deep silicon photon-counting CT (dSi-PCCT) on coronary stenosis quantification in anatomically realistic calcified coronary art…
Characterizing the Radiation Dose to Measurement Accuracy Relationship across Multiple Metrics in Opportunistic Chest CT
Boyuan Li, Carolyn C. Chang, Jake J. Kim +5
Objectives: This study aims to characterize the dose-performance relationship for opportunistic CT and disentangle the contributions of segmentation failure and dose-dependent HU b…
End-to-End Differentiable Photon Counting CT
Sen Wang, Yirong Yang, Jooho Lee +2
Quantitative imaging is an important feature of spectral X-ray and CT systems, especially photon-counting CT (PCCT) imaging systems, which is achieved through material decompositio…
Scout-Dose-TCM: Direct and Prospective Scout-Based Estimation of Personalized Organ Doses from Tube Current Modulated CT Exams
Maria Jose Medrano, Sen Wang, Liyan Sun +5
This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level doses under tube current modulation (TCM) and compares its performance to two established metho…
Unsupervised Training of a Dynamic Context-Aware Deep Denoising Framework for Low-Dose Fluoroscopic Imaging
Sun-Young Jeon, Sen Wang, Adam S. Wang +2
Fluoroscopy is critical for real-time X-ray visualization in medical imaging. However, low-dose images are compromised by noise, potentially affecting diagnostic accuracy. Noise re…
OpenDosimeter: Open Hardware Personal X-ray Dosimeter
Norah Ger, Alice Ku, Jasmyn Lopez +8
We present OpenDosimeter (www.opendosimeter.org), an open hardware solution for real-time personal X-ray dose monitoring based on a scintillation counter. Using an X-ray sensor ass…
PFCM: Poisson flow consistency models for low-dose CT image denoising
Dennis Hein, Grant Stevens, Adam Wang +1
X-ray computed tomography (CT) is widely used for medical diagnosis and treatment planning; however, concerns about ionizing radiation exposure drive efforts to optimize image qual…
A coronary artery phantom for task-based CT performance assessment and a comparative study of clinical CT, photon counting CT, and micro CT
Jed D. Pack, Paul Fitzgerald, Stephen Araujo +7
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 C…
Scout-Net: Prospective Personalized Estimation of CT Organ Doses from Scout Views
Abdullah-Al-Zubaer Imran, Sen Wang, Debashish Pal +4
Purpose: Estimation of patient-specific organ doses is required for more comprehensive dose metrics, such as effective dose. Currently, available methods are performed retrospectiv…
Coronary Atherosclerotic Plaque Characterization with Photon-counting CT: a Simulation-based Feasibility Study
Mengzhou Li, Mingye Wu, Jed Pack +5
Recent development of photon-counting CT (PCCT) brings great opportunities for plaque characterization with much-improved spatial resolution and spectral imaging capability. While…
Semi-Supervised Relational Contrastive Learning
Attiano Purpura-Pontoniere, Demetri Terzopoulos, Adam Wang +1
Disease diagnosis from medical images via supervised learning is usually dependent on tedious, error-prone, and costly image labeling by medical experts. Alternatively, semi-superv…
Multi-Energy Blended CBCT Spectral Imaging Using a Spectral Modulator with Flying Focal Spot (SMFFS)
Yifan Deng, Hao Zhou, Zhilei Wang +2
Conventional cone-beam CT (CBCT) can be easily compromised by scatter and beam hardening artifacts, and the entanglement of scatter and spectral effects introduces additional compl…
Single-Shot Quantitative X-ray Imaging Using a Primary Modulator and Dual-Layer Detector
Linxi Shi, N. Robert Bennett, Alexander Vezeridis +2
Purpose: Conventional x-ray imaging and fluoroscopy have limitations in quantitation due to several challenges, including scatter, beam hardening, and overlapping tissues. In this…
Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang +1
Deep learning-based models, when trained in a fully-supervised manner, can be effective in performing complex image analysis tasks, although contingent upon the availability of lar…
Window-Level is a Strong Denoising Surrogate
Ayaan Haque, Adam Wang, Abdullah-Al-Zubaer Imran
CT image quality is heavily reliant on radiation dose, which causes a trade-off between radiation dose and image quality that affects the subsequent image-based diagnostic performa…
An Analysis of Scatter Characteristics in X-ray CT Spectral Correction
Tao Zhang, Zhiqiang Chen, Hao Zhou +3
X-ray scatter remains a major physics challenge in volumetric computed tomography (CT), whose physical and statistical behaviors have been commonly leveraged in order to eliminate…
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang +1
Semi-supervised learning via learning from limited quantities of labeled data has been investigated as an alternative to supervised counterparts. Maximizing knowledge gains from co…
Deep Learning-Based Reconstruction of Interventional Tools from Four X-Ray Projections for Tomographic Interventional Guidance
Elias Eulig, Joscha Maier, Michael Knaup +4
Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a C-arm system. However, the projective data provide only limited in…
Assessing Robustness to Noise: Low-Cost Head CT Triage
Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren +4
Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems w…
Detective quantum efficiency of photon-counting CdTe and Si detectors for computed tomography: a simulation study
Mats Persson, Adam Wang, Norbert J. Pelc
Purpose: Developing photon-counting CT detectors requires understanding the impact of parameters such as converter material, absorption length and pixel size. We apply a novel line…