Jan Sijbers

University of Antwerp | UA · Department of Physics

Additive Manufacturing (AM) has emerged as a manufacturing process that allows the direct production of samples from digital models. To ensure that quality standards are met in all samples of a batch, X-ray computed tomography (X-CT) is often used in combination with automated anomaly detection. For the latter, deep learning (DL) anomaly detection...

Introduction Magnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a sin...

Continuous X-ray imaging is known to reduce mechanical vibrations and scan time compared to a step-and-shoot acquisition approach. However, motion during X-ray exposure leads to blurred projections and consequently to loss of spatial resolution and contrast in conventionally reconstructed images. Recent works that aim to reduce continuous motion bl...

Continuous acquisition is a scanning technique in which the object rotates without interruption while the x-ray projections are acquired. This results in a considerable reduction in scanning time, compared to a step-and-shoot acquisition. While a reduced scanning time is preferred, motion during acquisition leads to motion artifacts in the reconstr...

X‐ray imaging of wet foam dynamics with a high temporal resolution (e.g., 3D videos with a 10 Hz frame rate) requires fast rotation of either the foam sample or the X‐ray gantry. This, however, strongly limits the number of X‐ray projections per rotation that can be acquired. As a result, conventional computed tomography reconstruction methods gene...

Introduction Foot shape assessment is important to characterise the complex shape of a foot, which is in turn essential for accurate design of foot orthoses and footwear, as well as quantification of foot deformities (e.g., hallux valgus). Numerous approaches have been described over the past few decades to evaluate foot shape for orthotic and foot...

Objectives The aim of this study was to evaluate the use of a multicontrast deep learning (DL)–reconstructed 4-fold accelerated 2-dimensional (2D) turbo spin echo (TSE) protocol and the feasibility of 3-dimensional (3D) superresolution reconstruction (SRR) of DL-enhanced 6-fold accelerated 2D Dixon TSE magnetic resonance imaging (MRI) for comprehen...

X-ray imaging is becoming more commonplace for inline industrial inspection, where a sample placed on a conveyor belt is translated through a scanning setup. However, the conventional X-ray attenuation contrast is often insufficient to characterize soft materials such as polymers and carbon reinforced components. Edge illumination (EI) is an X-ray...

Cycling witnesses an increasing number of women breaking barriers and inspiring change. Despite these advancements, there remains significant work to achieve full equality and recognition for women cyclists. Key gender gaps persist in: ̵ Ergonomics and performance optimization: The cycling industry largely focuses on tacit and explicit knowledge on...

Magnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a single-image sup...

Motivation In the past decade, deep learning algorithms have surpassed the performance of many conventional image segmentation pipelines. Powerful models are now available for segmenting cells and nuclei in diverse 2D image types, but segmentation in 3D cell systems remains challenging due to the high cell density, the heterogenous resolution and c...

Purpose The study aims to identify differences in tibiofemoral joint morphology between responders (R group, no pain) to arthroscopic partial medial meniscectomy (APMM) versus medial postmeniscectomy syndrome patients (MPMS group, recurrent pain at 2 years postmeniscectomy) in a clinically neutrally aligned patient population. The second aim was to...

Electrical impedance imaging using high-density micro electrode arrays (HD-MEAs) is an emerging non-invasive technology to monitor cell cultures. This study aims to develop a practical electrical impedance tomography (EIT) strategy for three-dimensional (3D) imaging of cells cultured on two-dimensional (2D) HD-MEAs. Addressing for computational and...

Accurate 3D mesh registration is essential in many industrial applications of X-ray imaging, as it allows quality assessment and inspection of manufactured objects. Conventional methods rely mainly on time-consuming and expensive X-ray computed tomography (X-CT) or ancillary camera systems. Instead, we propose a novel approach for efficient 3D mult...

Manual anatomical landmarking for morphometric knee bone characterization in orthopedics is highly time-consuming and shows high operator variability. Therefore, automation could be a substantial improvement for diagnostics and personalized treatments relying on landmark-based methods. Applications include implant sizing and planning, meniscal allo...

Edge illumination x-ray phase contrast imaging (XPCI) provides increased contrast for low absorbing materials compared to attenuation images and sheds light on the material microstructure through dark field contrast. To apply XPCI in areas such as non-destructive testing and inline inspection, where scanned samples are increasingly compared to simu...

This research explores the process of generating artificial training data for the detection and classification of defective areas in X-ray computed tomography (XCT) scans in the agricultural domain using AI techniques. It aims to determine the minimum detectability limit for such defects through analyses regarding the Probability of Detection based...

Accurate and fast simulation of X-ray projection data from mesh models has many applications in academia and industry, ranging from 3D X-ray computed tomography (XCT) reconstruction algorithms to radiograph-based object inspection and quality control. While software tools for the simulation of X-ray projection data from mesh models are available, t...

Arterial spin labeling (ASL) is a promising, non-invasive perfusion magnetic resonance imaging technique for quantifying cerebral blood flow (CBF). Unfortunately, ASL suffers from an inherently low signal-to-noise ratio (SNR) and spatial resolution, undermining its potential. Increasing spatial resolution without significantly sacrificing SNR or sc...

Edge illumination (EI) is an X-ray imaging technique that, in addition to conventional absorption contrast, provides refraction and scatter contrast. It relies on an absorption mask in front of the sample that splits the X-ray beam into beamlets, which hits a second absorption mask positioned in front of the detector. The sample mask is then shifte...

Currently implemented accuracy metrics in open-source libraries for segmentation by supervised machine learning are typically one-dimensional scores [1]. While extremely relevant to evaluate applicability in clinics, anatomical location of segmentation errors is often neglected. This study aims to include the three-dimensional (3D) spatial informat...

Edge illumination is an emerging X-ray phase contrast imaging technique providing attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone beam geometry of lab systems limits the effectiveness of using conventional planar gratings. The non-parallel incidence of X-rays introduces shadowi...

Due to acquisition time constraints, T2-w FLAIR MRI of Multiple Sclerosis (MS) patients is often acquired with multi-slice 2D protocols with a low through-plane resolution rather than with high-resolution 3D protocols. Automated lesion segmentation on such low-resolution (LR) images, however, performs poorly and leads to inaccurate lesion volume es...

Background Actual Flip angle Imaging (AFI) is a sequence used for B1 mapping, also embedded in the Variable flip angle with AFI for simultaneous estimation of T1, B1 and equilibrium magnetization. Purpose To investigate the design of a preparation module for AFI to allow a fast approach to steady state (SS) without requiring the use of dummy acqui...

The properties of fiber reinforced polymers are strongly related to the length and orientation of the fibers within the polymer matrix, the latter of which can be studied using X-ray computed tomography (XCT). Unfortunately, resolving individual fibers is challenging because they are small compared to the XCT voxel resolution and because of the low...

Purpose To systematically review the techniques that address undersampling artifacts in accelerated quantitative magnetic resonance imaging (qMRI). Methods A literature search was conducted using the Embase, Medline, Web of Science Core Collection, Coherence Central Register of Controlled Trials, and Google Scholar databases for studies, published...

In this work, we compare the results of analyzing group differences in Alzheimer’s Disease (AD) with two different models for multi-shell diffusion MRI: the Diffusion Kurtosis Tensor (DKT) and Multi-Tissue Constrained Spherical Deconvolution (MT-CSD). Separate analysis for DKT metrics and measures derived from MT-CSD were performed to investigate d...

Additive Manufacturing (AM) has emerged as a manufacturing process that allows the direct production of samples from digital models. To ensure that quality standards are met in all manufactured samples of a batch, X-ray computed tomography (X-CT) is often used combined with automated anomaly detection. For the latter, deep learning (DL) anomaly det...

Terahertz (THz) computed tomography is an emerging nondestructive and non-ionizing imaging method. Most THz reconstruction methods rely on the Radon transform, originating from x-ray imaging, in which x rays propagate in straight lines. However, a THz beam has a finite width, and ignoring its shape results in blurred reconstructed images. Moreover,...

The prediction of functional outcome after mild traumatic brain injury (mTBI) is challenging. Conventional magnetic resonance imaging (MRI), does not explain well the variance in outcome as many patients with incomplete recovery will have normal appearing clinical neuroimaging. More advanced quantitative techniques such as diffusion MRI (dMRI), can...

X-ray computed tomography (XCT) is one of the most powerful imaging techniques in non-destructive testing (NDT) for detecting, analysing and visualising defects such as pores, fibres, cracks etc. in industrial specimens. Detecting defects in X-ray images, however, is still a challenging problem, as it strongly depends on the quality of the XCT imag...

Conventional X-ray computed tomography (XCT) is a non-destructive imaging technique to visualize and inspect the internal structure of materials in 3D, where materials are distinguished solely on the basis of their attenuation coefficient. However, with more specialized X-ray phase contrast imaging methods, sensitivity to complementary contrasts ca...

We propose a new method for denoising of 3D CT scans with few data. Like any other form of imaging data, CT scans are susceptible to noise and artifacts. Noise in CT scan images is not only stochastic, but can be frequency dependent and introduced by the measuring device itself or by signal processing algorithms. Unfortunately, most state-of-the-ar...

Current state-of-the-art motion-based dynamic computed tomography reconstruction techniques estimate the deformation by considering motion models in the entire object volume although occasionally the proper change is local. In this article, we address this issue by introducing the region-based Motion-compensated Iterative Reconstruction Technique (...

Longitudinal MRI is an important diagnostic imaging tool for evaluating the effects of treatment and monitoring disease progression. However, MRI, and particularly longitudinal MRI, is known to be time consuming. To accelerate imaging, compressed sensing (CS) theory has been applied to exploit sparsity, both on single image as on image sequence lev...

The prospect of continued manned space missions warrants an in-depth understanding of how prolonged microgravity affects the human brain. Functional magnetic resonance imaging (fMRI) can pinpoint changes reflecting adaptive neuroplasticity across time. We acquired resting-state fMRI data of cosmonauts before, shortly after, and eight months after s...

Tensor‐valued diffusion encoding facilitates data analysis by q‐space trajectory imaging. By modeling the diffusion signal of heterogeneous tissues with a diffusion tensor distribution (DTD) and modulating the encoding tensor shape, this novel approach allows disentangling variations in diffusivity from microscopic anisotropy, orientation dispersio...

A new framework for the parametric reconstruction of curved fibres from glass fibre-reinforced composite X-ray computed tomography data is proposed. It allows us to detect fibres in a fibre-reinforced polymer sample from a low-dose, low resolution computed tomography scan. An efficient curve representation is then used for each detected fibre, of w...

Transcatheter mitral valve replacement (TMVR) has emerged as a minimally invasive alternative for treating patients suffering from mitral valve disease. The number of TMVR procedures is expected to rise as devices currently in clinical trials obtain approval for commercialization. Automating the planning of such interventions becomes, therefore, mo...

Multi-slice (MS) super-resolution reconstruction (SRR) methods have been proposed to improve the trade-off between resolution, signal-to-noise ratio and scan time in magnetic resonance imaging. MS-SRR consists in the estimation of an isotropic high-resolution image from a series of anisotropic MS images with a low through-plane resolution, where th...

Background: Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume...

The design of new x-ray phase contrast imaging setups often relies on Monte Carlo simulations for prospective parameter studies. Monte Carlo simulations are known to be accurate but time consuming, leading to long simulation times, especially when many parameter variations are required. This is certainly the case for imaging methods relying on abso...