20 citations · 33 across the 16 of their papers we have counts for
10 papers · 1 filter
Plug-and-Play with 2.5D Artifact Reduction Prior for Fast and Accurate Industrial Computed Tomography Reconstruction
Haley Duba-Sullivan, Aniket Pramanik, Venkatakrishnan Singanallur +1
Cone-beam X-ray computed tomography (XCT) is an essential imaging technique for generating 3D reconstructions of internal structures, with applications ranging from medical to indu…
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…
Edge Projection-Based Adaptive View Selection for Cone-Beam CT
Jingsong Lin, Singanallur Venkatakrishnan, Gregery Buzzard +2
Industrial cone-beam X-ray computed tomography (CT) scans of additively manufactured components produce a 3D reconstruction from projection measurements acquired at multiple predet…
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…
YOLO2U-Net: Detection-Guided 3D Instance Segmentation for Microscopy
Amirkoushyar Ziabari, Derek C. Rose, Abbas Shirinifard +1
Microscopy imaging techniques are instrumental for characterization and analysis of biological structures. As these techniques typically render 3D visualization of cells by stackin…
Algorithm-driven Advances for Scientific CT Instruments: From Model-based to Deep Learning-based Approaches
S. V. Venkatakrishnan, K. Aditya Mohan, Amir Koushyar Ziabari +1
Multi-scale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. S…
Model-based Reconstruction for Enhanced X-ray CT of Tri-structural Isotropic (TRISO) Particles
Singanallur V. Venkatakrishnan, Amirkoushyar Ziabari, Philip Bingham +1
Tri-Structural Isotropic (TRISO) fuel particles are a key component of next generation nuclear fuels. Using X-ray computed tomography (CT) to characterize TRISO particles is challe…
2.5D Deep Learning for CT Image Reconstruction using a Multi-GPU implementation
Amirkoushyar Ziabari, Dong Hye Ye, Somesh Srivastava +3
While Model Based Iterative Reconstruction (MBIR) of CT scans has been shown to have better image quality than Filtered Back Projection (FBP), its use has been limited by its high…
Model Based Iterative Reconstruction With Spatially Adaptive Sinogram Weights for Wide-Cone Cardiac CT
Amirkoushyar Ziabari, Dong Hye Ye, Lin Fu +4
With the recent introduction of CT scanners with large cone angles, wide coverage detectors now provide a desirable scanning platform for cardiac CT that allows whole heart imaging…