Searched for: subject%3A%22compressed%255C%2Bsensing%22
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van der Meulen, P.Q. (author)
Whereas aberrating layers are typically viewed as an impediment to medical ultrasound imaging, they can, surprisingly, also be used to our benefit. As long as we can model the effect of an aberrating layer, we can utilize ‘model-based imaging’, the imaging technique explored throughout this thesis, to reconstruct ultrasound images where...
doctoral thesis 2023
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Lamberti, Lucas (author)
Direction of Arrival (DoA) estimation is an important topic in radar application and has significant importance for advanced driver assistant systems in the automotive industry. While there is an increasing need for higher resolution and increased target detection and DoA estimation performance, such improvements often require increased hardware...
master thesis 2022
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Suvarna, Anusha Ravish (author), Koppelaar, Arie (author), Jansen, Feike (author), Wang, J. (author), Yarovoy, Alexander (author)
High angular resolution is in high demand in automotive radar. To achieve a high azimuth resolution a large aperture antenna array is required. Although MIMO technique can be used to form larger virtual apertures, a large number of transmitter-receiver channels are needed, which is still technologically challenging and costly. To circumvent this...
conference paper 2022
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Joseph, G. (author), Varshney, Pramod K. (author)
In this paper, we consider the problem of estimating the states of a linear dynamical system whose inputs are jointly sparse and outputs at a few unknown time instants are missing. We model the missing data mechanism using a Markov chain with two states representing the missing and non-missing data. This mechanism with memory governed by the...
conference paper 2022
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Karkalousos, D. (author), Noteboom, S. (author), Hulst, H. E. (author), Vos, F.M. (author), Caan, M.W.A. (author)
Objective. Machine Learning methods can learn how to reconstruct magnetic resonance images (MRI) and thereby accelerate acquisition, which is of paramount importance to the clinical workflow. Physics-informed networks incorporate the forward model of accelerated MRI reconstruction in the learning process. With increasing network complexity,...
journal article 2022
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Roldan Montero, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The problem of extended target cross-section estimation has been considered. A two-step method based on the Total Variation Compressive Sensing theory has been proposed to solve it. First, a coarse estimation of the target cross-section is performed with classical beamforming methods, and then Compressive Sensing algorithms have been applied...
conference paper 2022
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de Gijsel, Stefan L. (author), Vijn, A.R.P.J. (author), Tan, Reinier G. (author)
This paper proposes an algorithm to localize a magnetic dipole using a limited number of noisy measurements from magnetic field sensors. The algorithm is based on the theory of compressed sensing, and exploits the sparseness of the magnetic dipole in space. Beforehand, a basis consisting of magnetic dipole fields belonging to individual...
journal article 2022
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Ravish Suvarna, Anusha (author)
In today's automotive applications, radar is widely used to estimate the target position and velocity with respect to the radar position. Estimating the position of the target in terms of range and velocity is fairly advanced and accurate. However, resolving two closely spaced targets in the azimuth domain which have the same range and relative...
master thesis 2021
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de Gijsel, Stefan (author)
A severe incident with the cargo ship MSC Zoe, which lost hundreds of containers near the Dutch coast, shows how important it can be to detect and localise hidden objects at sea quickly. Also in defence applications localisation of hidden objects in water is important. If the objects are made of magnetic materials, they disturb the Earth...
master thesis 2021
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Pancras, Kevin (author)
The Recurrent Inference Machine (RIM) has been developed as an alternative to the clinically used Compressed Sensing (CS) algorithm, using Deep Learning (DL). A common issue with DL networks is the generalization of the network to features that have not been trained for. In this study we evaluate the robustness of the RIM to white matter lesions...
master thesis 2021
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Kumari, Preeti (author), Myers, N.J. (author), Heath, Robert W. (author)
Millimeter-wave (mmWave) joint communication-radar (JCR) will enable high data rate communication and high-resolution radar sensing for applications such as autonomous driving. Prior JCR systems that are based on the mmWave communications hardware, however, suffer from a limited angular field-of-view and low estimation accuracy for radars due...
journal article 2021
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Zhang, Kaiwen (author), Coutino, Mario (author), Isufi, E. (author)
Graph sampling strategies require the signal to be relatively sparse in an alternative domain, e.g. bandlimitedness for reconstructing the signal. When such a condition is violated or its approximation demands a large bandwidth, the reconstruction often comes with unsatisfactory results even with large samples. In this paper, we propose an...
conference paper 2021
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Koolstra, Kirsten (author), Remis, R.F. (author)
Purpose: To learn a preconditioner that accelerates parallel imaging (PI) and compressed sensing (CS) reconstructions. Methods: A convolutional neural network (CNN) with residual connections was used to train a preconditioning operator. Training and validation data were simulated using 50% brain images and 50% white Gaussian noise images....
journal article 2021
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de Leeuw den Bouter, M.L. (author), van den Berg, P.M. (author), Remis, R.F. (author)
In this paper we discuss an imaging method when the object has known support and its spatial Fourier transform is only known on a certain k-space undersampled pattern. The simple conjugate gradient least squares algorithm applied to the corresponding truncated Fourier transform equation produces reconstructions that are basically of a similar...
journal article 2021
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Dhingra, Kriti (author)
Magnetic Resonance Imaging is a painless procedure to produce high-resolution diagnostic images. Today, it is one of the essential clinical imaging modalities. One of the major challenges involved with this imaging modality is its long scanning time. Parallel imaging in combination with compressed sensing has overcome this challenge to a great...
master thesis 2020
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Sharma, Shubham (author), Coutino, Mario (author), Chepuri, Sundeep Prabhakar (author), Leus, G.J.T. (author), Hari, K. V.S. (author)
The design of feasible trajectories to traverse the k-space for sampling in magnetic resonance imaging (MRI) is important while considering ways to reduce the scan time. Over the recent years, non-Cartesian trajectories have been observed to result in benign artifacts and being less sensitive to motion. In this paper, we propose a generalized...
journal article 2020
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van der Meulen, P.Q. (author), Kruizinga, P. (author), Bosch, Johannes G. (author), Leus, G.J.T. (author)
We study the design of a coding mask for pulse-echo ultrasound imaging. We are interested in the scenario of a single receiving transducer with an aberrating layer, or ‘mask,’ in front of the transducer's receive surface, with a separate co-located transmit transducer. The mask encodes spatial measurements into a single output signal, containing...
journal article 2020
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Ajorloo, Abdollah (author), Amini, Arash (author), Tohidi, Ehsan (author), Bastani, Mohammad Hassan (author), Leus, G.J.T. (author)
Compressive sensing (CS) has been widely used in multiple-input-multiple-output (MIMO) radar in recent years. Unlike traditional MIMO radar, detection/estimation of targets in a CS-based MIMO radar is accomplished via sparse recovery. In this article, for a CS-based colocated MIMO radar with linear arrays, we attempt to improve the target...
journal article 2020
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Das, Bishwadeep (author), Isufi, E. (author), Leus, G.J.T. (author)
Diffusion-based semi-supervised learning on graphs consists of diffusing labeled information of a few nodes to infer the labels on the remaining ones. The performance of these methods heavily relies on the initial labeled set, which is either generated randomly or using heuristics. The first sometimes leads to unsatisfactory results because...
conference paper 2020
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Sharma, S. (author), Hari, K.V.S. (author), Leus, G.J.T. (author)
The development of compressed sensing (CS) techniques for magnetic resonance imaging (MRI) is enabling a speedup of MRI scanning. To increase the incoherence in the sampling, a random selection of points on the k-space is deployed and a continuous trajectory is obtained by solving a traveling salesman problem (TSP) through these points. A...
conference paper 2020
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