91 citations · 293 across the 30 of their papers we have counts for
32 papers
Efficient Flow Matching for Sparse-View CT Reconstruction
Jiayang Shi, Lincen Yang, Zhong Li +3
Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expressive priors for solving ill-posed in…
An invertible generative model for forward and inverse problems
Christoph Brune, Marcello Carioni, Tristan van Leeuwen +1
We formulate inverse problems in a Bayesian framework and aim to train an invertible generative model that is capable of simulation (i.e., sampling from the likelihood) and inferen…
Exploring Out-of-distribution Detection for Sparse-view Computed Tomography with Diffusion Models
Ezgi Demircan-Tureyen, Felix Lucka, Tristan van Leeuwen
Recent works demonstrate the effectiveness of diffusion models as unsupervised solvers for inverse imaging problems. Sparse-view computed tomography (CT) has greatly benefited from…
Quantitative phase imaging via a multimode fiber
Aleksandra Ivanina, Maxim Marshall, Ksenia Abrashitova +2
Label-free quantitative phase imaging is a vital tool for optical microscopy and metrology applications. A hair-thin multimode fiber stands out as a very attractive platform for mi…
Experimental Validation of Ultrasound Beamforming with End-to-End Deep Learning for Single Plane Wave Imaging
Ryan A. L. Schoop, Gijs Hendriks, Tristan van Leeuwen +2
Ultrafast ultrasound imaging insonifies a medium with one or a combination of a few plane waves at different beam-steered angles instead of many focused waves. It can achieve much…
An Analysis of Constraint-Relaxation in PDE-Based Inverse Problems
Tristan van Leeuwen, Yunan Yang
Inverse problems are ubiquitous in science and engineering. Many of these are naturally formulated as a PDE-constrained optimization problem. These non-linear, large-scale, constra…
X-ray Image Generation as a Method of Performance Prediction for Real-Time Inspection: a Case Study
Vladyslav Andriiashen, Robert van Liere, Tristan van Leeuwen +1
X-ray imaging can be efficiently used for high-throughput in-line inspection of industrial products. However, designing a system that satisfies industrial requirements and achieves…
Time-Resolved Reconstruction of Motion, Force, and Stiffness using Spectro-Dynamic MRI
Max H. C. van Riel, Tristan van Leeuwen, Cornelis A. T. van den Berg +1
Measuring the dynamics and mechanical properties of muscles and joints is important to understand the (patho)physiology of muscles. However, acquiring dynamic time-resolved MRI dat…
Joint 2D to 3D image registration workflow for comparing multiple slice photographs and CT scans of apple fruit with internal disorders
Dirk Elias Schut, Rachael Maree Wood, Anna Katharina Trull +4
A large percentage of apples are affected by internal disorders after long-term storage, which makes them unacceptable in the supply chain. CT imaging is a promising technique for…
Maximum-likelihood estimation in ptychography in the presence of Poisson-Gaussian noise statistics
Jacob Seifert, Yifeng Shao, Rens van Dam +3
Optical measurements often exhibit mixed Poisson-Gaussian noise statistics, which hampers image quality, particularly under low signal-to-noise ratio (SNR) conditions. Computationa…
Sequential Experimental Design for X-Ray CT Using Deep Reinforcement Learning
Tianyuan Wang, Felix Lucka, Tristan van Leeuwen
In X-ray Computed Tomography (CT), projections from many angles are acquired and used for 3D reconstruction. To make CT suitable for in-line quality control, reducing the number of…
2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning
Maximilian B. Kiss, Sophia B. Coban, K. Joost Batenburg +2
Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consi…
Quantifying the effect of X-ray scattering for data generation in real-time defect detection
Vladyslav Andriiashen, Robert van Liere, Tristan van Leeuwen +1
Background: X-ray imaging is widely used for the non-destructive detection of defects in industrial products on a conveyor belt. In-line detection requires highly accurate, robust,…
A data-driven approach to solving a 1D inverse scattering problem
Tristan van Leeuwen, Andreas Tataris
In this paper, we extend the ROM-based approach for inverse scattering with Neumann boundary conditions, introduced by Druskin at. al. (Inverse Problems 37, 2021), to the 1D Schr{ö…
Towards retrospective motion correction and reconstruction for clinical 3D brain MRI protocols with a reference contrast
Gabrio Rizzuti, Tim Schakel, Niek R. F. Huttinga +3
Motion artifacts often spoil the radiological interpretation of MR images, and in the most severe cases the scan needs be repeated, with additional costs for the provider. We discu…
A tomographic workflow to enable deep learning for X-ray based foreign object detection
Mathé T. Zeegers, Tristan van Leeuwen, Daniël M. Pelt +3
Detection of unwanted (`foreign') objects within products is a common procedure in many branches of industry for maintaining production quality. X-ray imaging is a fast, non-invasi…
WaRIance: wavefield reconstruction inversion with stochastic variable projection
Gabrio Rizzuti, Tristan van Leeuwen
We propose a variation on wavefield reconstruction inversion for seismic inversion, which takes advantage of randomized linear algebra as a way to overcome the typical limitations…
ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
Mathé T. Zeegers, Ajinkya Kadu, Tristan van Leeuwen +1
Advances in multi-spectral detectors are causing a paradigm shift in X-ray Computed Tomography (CT). Spectral information acquired from these detectors can be used to extract volum…
Single Plane-Wave Imaging using Physics-Based Deep Learning
Georgios Pilikos, Chris L. de Korte, Tristan van Leeuwen +1
In plane-wave imaging, multiple unfocused ultrasound waves are transmitted into a medium of interest from different angles and an image is formed from the recorded reflections. The…
Deep Learning for Multi-View Ultrasonic Image Fusion
Georgios Pilikos, Lars Horchens, Tristan van Leeuwen +1
Ultrasonic imaging is being used to obtain information about the acoustic properties of a medium by emitting waves into it and recording their interaction using ultrasonic transduc…
Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry
Vladyslav Andriiashen, Robert van Liere, Tristan van Leeuwen +1
X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of fore…
Deep data compression for approximate ultrasonic image formation
Georgios Pilikos, Lars Horchens, Kees Joost Batenburg +2
In many ultrasonic imaging systems, data acquisition and image formation are performed on separate computing devices. Data transmission is becoming a bottleneck, thus, efficient da…
Fast ultrasonic imaging using end-to-end deep learning
Georgios Pilikos, Lars Horchens, Kees Joost Batenburg +2
Ultrasonic imaging algorithms used in many clinical and industrial applications consist of three steps: A data pre-processing, an image formation and an image post-processing step.…
Relaxed regularization for linear inverse problems
Nick Luiken, Tristan van Leeuwen
We consider regularized least-squares problems of the form . Recently, Zheng et al., 2019, proposed an algorithm called…