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Author |
Van den Broek, W.; Reed, B.W.; Béché, A.; Velazco, A.; Verbeeck, J.; Koch, C.T. |
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Title |
Various compressed sensing setups evaluated against Shannon sampling under constraint of constant illumination |
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A1 Journal article |
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Year |
2019 |
Publication |
IEEE transactions on computational imaging |
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Volume |
5 |
Issue |
3 |
Pages |
502-514 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Under the constraint of constant illumination, an information criterion is formulated for the Fisher information that compressed sensing measurements in optical and transmission electron microscopy contain about the underlying parameters. Since this approach requires prior knowledge of the signal's support in the sparse basis, we develop a heuristic quantity, the detective quantum efficiency (DQE), that tracks this information criterion well without this knowledge. In this paper, it is shown that for the investigated choice of sensing matrices, and in the absence of read-out noise, i.e., with only Poisson noise present, compressed sensing does not raise the amount of Fisher information in the recordings above that of Shannon sampling. Furthermore, enabled by the DQE's analytical tractability, the experimental designs are optimized by finding out the optimal fraction of on pixels as a function of dose and read-out noise. Finally, we introduce a regularization and demonstrate, through simulations and experiment, that it yields reconstructions attaining minimum mean squared error at experimental settings predicted by the DQE as optimal. |
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Wos |
000480352600013 |
Publication Date |
2019-01-24 |
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Edition |
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ISSN |
2333-9403 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
4.546 |
Times cited |
7 |
Open Access |
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Notes |
; This work was supported by the Hercules fund from the Flemish Government (Qu-Ant-EM microscope used for the experimental data). The work of W. Van den Broek was supported by the DFG under Grant BR 5095/2-1 (Compressed sensing in ptychography and transmission electron microscopy). The work of A. Beche, A. Velazco, and J. Verbeeck was supported by the FWO under Grant G093417N (Compressed sensing enabling low dose imaging in transmission electron microscopy). The work of Christoph T. Koch was supported by the DFG under Grant CRC 951. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Chrysanthe Preza. ; |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:161792 |
Serial |
5368 |
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Author |
Kadu, A.; Lucka, F.; Batenburg, K.J. |
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Title |
Single-shot tomography of discrete dynamic objects |
Type |
A1 Journal article |
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Year |
2024 |
Publication |
IEEE transactions on computational imaging |
Abbreviated Journal |
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Volume |
10 |
Issue |
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Pages |
941-952 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
This paper presents a novel method for the reconstruction of high-resolution temporal images in dynamic tomographic imaging, particularly for discrete objects with smooth boundaries that vary over time. Addressing the challenge of limited measurements per time point, we propose a technique that incorporates spatial and temporal information of the dynamic objects. Our method uses the explicit assumption of homogeneous attenuation values of discrete objects. We achieve this computationally through the application of the level-set method for image segmentation and the representation of motion via a sinusoidal basis. The result is a computationally efficient and easily optimizable variational framework that enables the reconstruction of high-quality 2D or 3D image sequences with a single projection per frame. Compared to variational regularization-based methods using similar image models, our approach demonstrates superior performance on both synthetic and pseudo-dynamic real X-ray tomography datasets. The implications of this research extend to improved visualization and analysis of dynamic processes in tomographic imaging, finding potential applications in diverse scientific and industrial domains. The supporting data and code are provided. |
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https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=brocade2&SrcAuth=WosAPI&KeyUT=WOS:001256 |
Publication Date |
2024-06-13 |
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ISSN |
2573-0436; 2333-9403 |
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Additional Links |
UA library record; WoS full record; WoS full record |
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Impact Factor |
5.4 |
Times cited |
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Open Access |
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Approved |
Most recent IF: 5.4; 2024 IF: NA |
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Call Number |
UA @ admin @ c:irua:207017 |
Serial |
9315 |
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