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Proton computed tomography (pCT) is a novel medical imaging modality for mapping the distribution of proton relative stopping power (RSP) in medical objects of interest. Compared to conventional X-ray computed tomography, where range…

X-ray phase-contrast imaging has the potential to improve image contrast with lower dose by probing an object's refractive properties as well as its absorptive properties. To reconstruct a phase-contrast image from a raw dataset, a phase…

Medical Physics · Physics 2025-08-19 Giavanna Jadick , Patrick La Rivière

X-ray ptychography is a powerful and robust coherent imaging method providing access to the complex object and probe (illumination). Ptychography reconstruction is typically performed using first-order methods due to their computational…

Optics · Physics 2025-04-07 Marcus Carlsson , Herwig Wendt , Peter Cloetens , Viktor Nikitin

Referring image segmentation is an advanced semantic segmentation task where target is not a predefined class but is described in natural language. Most of existing methods for this task rely heavily on convolutional neural networks, which…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Namyup Kim , Dongwon Kim , Cuiling Lan , Wenjun Zeng , Suha Kwak

Hyperspectral neutron computed tomography is a tomographic imaging technique in which thousands of wavelength-specific neutron radiographs are measured for each tomographic view. In conventional hyperspectral reconstruction, data from each…

There is a need for open-source libraries in emission tomography that (i) use modern and popular backend code to encourage community contributions and (ii) offer support for the multitude of reconstruction techniques available in recent…

Stochastic microstructure reconstruction has become an indispensable part of computational materials science, but ongoing developments are specific to particular material systems. In this paper, we address this generality problem by…

Materials Science · Physics 2018-05-09 Xiaolin Li , Yichi Zhang , He Zhao , Craig Burkhart , L Catherine Brinson , Wei Chen

Ptychography is an enabling coherent diffraction imaging technique for both fundamental and applied sciences. Its applications in optical microscopy, however, fall short for its low imaging throughput and limited resolution. Here, we report…

We demonstrate a motion-free intensity diffraction tomography technique that enables direct inversion of 3D phase and absorption from intensity-only measurements for weakly scattering samples. We derive a novel linear forward model,…

Image and Video Processing · Electrical Eng. & Systems 2018-06-26 Ruilong Ling , Waleed Tahir , Hsing-Ying Lin , Hakho Lee , Lei Tian

X-ray phase-contrast tomography (XPCT) is widely used for high contrast 3D imaging using either synchrotron or laboratory microfocus X-ray sources. XPCT enables an order of magnitude improvement in image contrast of the reconstructed…

Image and Video Processing · Electrical Eng. & Systems 2024-10-28 K. Aditya Mohan , Jean-Baptiste Forien , Venkatesh Sridhar , Jefferson A. Cuadra , Dilworth Parkinson

Hyperspectral neutron computed tomography enables 3D non-destructive imaging of the spectral characteristics of materials. In traditional hyperspectral reconstruction, the data for each neutron wavelength bin is reconstructed separately.…

Storage systems often rely on multiple copies of the same compressed data, enabling recovery in case of binary data errors, of course, at the expense of a higher storage cost. In this paper we show that a wiser method of duplication entails…

Multimedia · Computer Science 2019-02-08 Yehuda Dar , Alfred M. Bruckstein

We solve the image denoising problem with a dictionary learning technique by writing a convex functional of a new form. This functional contains beside the usual sparsity inducing term and fidelity term, a new term which induces similarity…

Numerical Analysis · Mathematics 2015-06-02 Alessandro Mirone , Emmanuel Brun , Paola Coan

The Image-Based Rendering (IBR) approach using Shearlet Transform (ST) is one of the most effective methods for Densely-Sampled Light Field (DSLF) reconstruction. The ST-based DSLF reconstruction typically relies on an iterative…

Multimedia · Computer Science 2020-03-20 Yuan Gao , Robert Bregovic , Reinhard Koch , Atanas Gotchev

The image-based rendering approach using Shearlet Transform (ST) is one of the state-of-the-art Densely-Sampled Light Field (DSLF) reconstruction methods. It reconstructs Epipolar-Plane Images (EPIs) in image domain via an iterative…

Signal Processing · Electrical Eng. & Systems 2023-07-19 Yuan Gao , Robert Bregovic , Atanas Gotchev

Next generation radio interferometric telescopes are entering an era of big data with extremely large data sets. While these telescopes can observe the sky in higher sensitivity and resolution than before, computational challenges in image…

Instrumentation and Methods for Astrophysics · Physics 2019-12-17 Luke Pratley , Jason D. McEwen , Mayeul d'Avezac , Xiaohao Cai , David Perez-Suarez , Ilektra Christidi , Roland Guichard

Scene reconstruction has emerged as a central challenge in computer vision, with approaches such as Neural Radiance Fields (NeRF) and Gaussian Splatting achieving remarkable progress. While Gaussian Splatting demonstrates strong performance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Alexander Valverde , Brian Xu , Yuyin Zhou , Meng Xu , Hongyun Wang

Phase reconstruction is important in transmission electron microscopy for structural studies. We describe electron Fourier ptychography and its application to phase reconstruction of both radiation-resistant and beam-sensitive materials. We…

Ptychography is a computational method of microscopy that recovers high-resolution transmission images of samples from a series of diffraction patterns. While conventional phase retrieval algorithms can iteratively recover the images, they…

Image and Video Processing · Electrical Eng. & Systems 2024-10-24 Ryuma Nakahata , Shehtab Zaman , Mingyuan Zhang , Fake Lu , Kenneth Chiu

We propose a distributionally robust approach to learning hyperparameters for first-order methods in convex optimization. Given a dataset of problem instances, we minimize a Wasserstein distributionally robust version of the performance…

Machine Learning · Computer Science 2026-05-08 Vinit Ranjan , Jisun Park , Bartolomeo Stellato