Obaidullah Rahman
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View article: Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components
Combining Deep Learning and scatterControl for High-Throughput X-ray CT Based Non-Destructive Characterization of Large-Scale Casted Metallic Components Open
View article: Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization
Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization Open
View article: Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning
Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning Open
View article: Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography
Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography Open
View article: An Adaptive View Selection Algorithm for Large-scale Cone-Beam CT Reconstruction
An Adaptive View Selection Algorithm for Large-scale Cone-Beam CT Reconstruction Open
Industrial cone-beam X-ray computed tomography (CT) produces 3D reconstructions of objects using projection measurements taken at multiple predetermined rotation angles around a single axis. Achieving high-quality reconstructions with trad…
View article: A Fast, Scalable, and Robust Deep Learning-based Iterative Reconstruction Framework for Accelerated Industrial Cone-beam X-ray Computed Tomography
A Fast, Scalable, and Robust Deep Learning-based Iterative Reconstruction Framework for Accelerated Industrial Cone-beam X-ray Computed Tomography Open
Cone-beam X-ray Computed Tomography (XCT) with large detectors and corresponding large-scale 3D reconstruction plays a pivotal role in micron-scale characterization of materials and parts across various industries. In this work, we present…
View article: Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography
Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography Open
Obtaining high-quality 3D reconstructions from electron tomography of crystalline particles embedded in lighter support elements is crucial for various material systems such as catalysts for fuel cell applications. However, significant cha…
View article: 2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts
2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts Open
X-ray computed tomography (XCT) is a key tool in non-destructive evaluation of additively manufactured (AM) parts, allowing for internal inspection and defect detection. Despite its widespread use, obtaining high-resolution CT scans can be…
View article: A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells
A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells Open
The loss of platinum (Pt) electrochemically active surface area (ECSA) is a critical degradation mode that often becomes a limiting factor for heavy‐duty proton exchange membrane fuel cell vehicles. High surface area carbon supports have b…
View article: Reduction kinetics of hematite powder using argon/hydrogen plasma with prospects for near net shaping of sustainable iron
Reduction kinetics of hematite powder using argon/hydrogen plasma with prospects for near net shaping of sustainable iron Open
View article: Creep deformation and cavitation in an additively manufactured Al-8.6Cu-0.4Mn-0.9Zr (wt%) alloy
Creep deformation and cavitation in an additively manufactured Al-8.6Cu-0.4Mn-0.9Zr (wt%) alloy Open
View article: Dual X-Ray Computed Tomography-Aided Classification of Melt Pool Boundaries and Flaws in Crept Additively Manufactured Parts
Dual X-Ray Computed Tomography-Aided Classification of Melt Pool Boundaries and Flaws in Crept Additively Manufactured Parts Open
View article: Deep learning based workflow for accelerated industrial X-ray Computed Tomography
Deep learning based workflow for accelerated industrial X-ray Computed Tomography Open
X-ray computed tomography (XCT) is an important tool for high-resolution non-destructive characterization of additively-manufactured metal components. XCT reconstructions of metal components may have beam hardening artifacts such as cuppin…
View article: Statistically Adaptive Filtering for Low Signal Correction in X-ray Computed Tomography
Statistically Adaptive Filtering for Low Signal Correction in X-ray Computed Tomography Open
Low x-ray dose is desirable in x-ray computed tomographic (CT) imaging due to health concerns. But low dose comes with a cost of low signal artifacts such as streaks and low frequency bias in the reconstruction. As a result, low signal cor…
View article: MBIR Training for a 2.5D DL network in X-ray CT
MBIR Training for a 2.5D DL network in X-ray CT Open
In computed tomographic imaging, model based iterative reconstruction methods have generally shown better image quality than the more traditional, faster filtered backprojection technique. The cost we have to pay is that MBIR is computatio…
View article: Design of Novel Loss Functions for Deep Learning in X-ray CT
Design of Novel Loss Functions for Deep Learning in X-ray CT Open
Deep learning (DL) shows promise of advantages over conventional signal processing techniques in a variety of imaging applications. The networks' being trained from examples of data rather than explicitly designed allows them to learn sign…
View article: Direct Iterative Reconstruction of Multiple Basis Material Images in Photon-counting Spectral CT
Direct Iterative Reconstruction of Multiple Basis Material Images in Photon-counting Spectral CT Open
In this work, we perform direct material reconstruction from spectral CT data using a model based iterative reconstruction (MBIR) approach. Material concentrations are measured in volume fractions, whose total is constrained by a maximum o…
View article: Deep Learning Based Workflow for Accelerated Industrial X-Ray Computed Tomography
Deep Learning Based Workflow for Accelerated Industrial X-Ray Computed Tomography Open
X-ray computed tomography (XCT) is an important tool for high-resolution non-destructive characterization of additively-manufactured metal components. XCT reconstructions of metal components may have beam hardening artifacts such as cuppin…
View article: Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR
Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR Open
Electron tomography is a powerful tool for characterization of three-dimensional (3D) nanoscale materials and devices. Bright-field (BF) and high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) are two wid…
View article: Design of novel loss functions for deep learning in x-ray CT
Design of novel loss functions for deep learning in x-ray CT Open
Deep learning (DL) shows promise of advantages over conventional signal processing techniques in a variety of imaging applications. The networks' being trained from examples of data rather than explicitly designed allows them to learn sign…
View article: Spatio-temporal Visualization of Regional Myocardial Velocities
Spatio-temporal Visualization of Regional Myocardial Velocities Open
Cardiovascular disease is the leading cause of death worldwide according to the World Health Organization (WHO). Nearly half of all heart failures occur due to the decline in the performance of the left ventricle (LV). Therefore, early det…