1 citations · 1 across the 9 of their papers we have counts for
9 papers
Toward a Foundation Plug-and-Play Prior for Computed Tomography Reconstruction via a Multimodal Diffusion Model
Haley Duba-Sullivan, Patxi Fernandez-Zelaia, Obaidullah Rahman +1
Computed tomography (CT) throughput is limited by scan time, which grows with both the number of projections acquired and the detector integration time for each projection. Reconst…
A Fast, Scalable, and Robust Deep Learning-based Iterative Reconstruction Framework for Accelerated Industrial Cone-beam X-ray Computed Tomography
Aniket Pramanik, Obaidullah Rahman, Singanallur V. Venkatakrishnan +1
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 an…
A Learnt Half-Quadratic Splitting-Based Algorithm for Fast and High-Quality Industrial Cone-beam CT Reconstruction
Aniket Pramanik, Singanallur V. Venkatakrishnan, Obaidullah Rahman +1
Industrial X-ray cone-beam CT (XCT) scanners are widely used for scientific imaging and non-destructive characterization. Industrial CBCT scanners use large detectors containing mi…
2.5D Super-Resolution Approaches for X-ray Computed Tomography-based Inspection of Additively Manufactured Parts
Haley Duba-Sullivan, Obaidullah Rahman, Singanallur Venkatakrishnan +1
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 it…
Direct Iterative Reconstruction of Multiple Basis Material Images in Photon-counting Spectral CT
Obaidullah Rahman, Ken Sauer, Connor Evans +1
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…
Deep learning based workflow for accelerated industrial X-ray Computed Tomography
Obaidullah Rahman, Singanallur V. Venkatakrishnan, Luke Scime +5
X-ray computed tomography (XCT) is an important tool for high-resolution non-destructive characterization of additively-manufactured metal components. XCT reconstructions of metal…
Design of Novel Loss Functions for Deep Learning in X-ray CT
Obaidullah Rahman, Ken D. Sauer, Madhuri Nagare +4
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 dat…
Statistically Adaptive Filtering for Low Signal Correction in X-ray Computed Tomography
Obaidullah Rahman, Ken D. Sauer, Charles A. Bouman +2
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 freque…
MBIR Training for a 2.5D DL network in X-ray CT
Obaidullah Rahman, Madhuri Nagare, Ken D. Sauer +4
In computed tomographic imaging, model based iterative reconstruction methods have generally shown better image quality than the more traditional, faster filtered backprojection te…