| 1. |
- Brunskog, Rickard, et al.
(författare)
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First experimental evaluation of a high-resolution deep silicon photon-counting sensor
- 2024
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Ingår i: Journal of Medical Imaging. - : SPIE-Intl Soc Optical Eng. - 2329-4302 .- 2329-4310. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Current photon-counting computed tomography detectors are limited to a pixel size of around 0.3 to 0.5 mm due to excessive charge sharing degrading the dose efficiency and energy resolution as the pixels become smaller. In this work, we present measurements of a prototype photon-counting detector that leverages the charge sharing to reach a theoretical sub-pixel resolution in the order of 1 μm. The goal of the study is to validate our Monte-Carlo simulation using measurements, enabling further development. Approach: We measure the channel response at the MAX IV Lab, in the DanMAX beamline, with a 35 keV photon beam, and compare the measurements with a 2D Monte Carlo simulation combined with a charge transport model. Only a few channels on the prototype are connected to keep the number of wire bonds low. Results: The measurements agree generally well with the simulations with the beam close to the electrodes but diverge as the beam is moved further away. The induced charge cloud signals also seem to increase linearly as the beam is moved away from the electrodes. Conclusions: The agreement between measurements and simulations indicates that the Monte-Carlo simulation can accurately model the channel response of the detector with the photon interactions close to the electrodes, which indicates that the unconnected electrodes introduce unwanted effects that need to be further explored. With the same Monte-Carlo simulation previously indicating a resolution of around 1 μm with similar geometry, the results are promising that an ultra-high resolution detector is not far in the future.
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| 2. |
- Cabo Rios, Alberto, 1990, et al.
(författare)
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Ex-situ characterization and simulation of density fluctuations evolution during sintering of binder jetted 316L
- 2024
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Ingår i: Materials and Design. - 1873-4197 .- 0264-1275. ; 238
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Tidskriftsartikel (refereegranskat)abstract
- Efficient density evolution during sintering of the as-printed component is vital to reach full densification and required properties of binder jet (BJT) components. However, due to the high porosity and brittle nature of the green compact, analysis of the microstructure development during sintering is very difficult, resulting in lack of understanding of the densification process. Density development from green state (57 ± 1.6 %) up to full density (99 ± 0.3 %) was characterized by high-resolution synchrotron X-Ray computed tomography (SXCT) on BJT 316L samples from ex-situ interrupted sintering tests. Periodicity of density fluctuations along the building direction was revealed for the first time and was related to the layer thickness of ∼ 42 µm during printing that decreased down to ∼ 33 µm during sintering. Sintering simulations, utilizing a continuum sintering model developed for BJT, allowed to replicate the density evolution during sintering with a mean error of 2 % and its fluctuation evolution from green (1.66 %) to sintered (0.56 %) state. Additionally, simulation of extreme particle size segregation (1 µm to 130 µm) suggested that non-optimized printing could lead to undesirable density fluctuation amplitude rapid increase (∼10 %) during sintering. This might trigger the nucleation of defects (e.g., layer delamination, cracking, or excessive residual porosity) during the sintering process.
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| 3. |
- Jin, Zihui, et al.
(författare)
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First experimental evaluation of count-rate performance for micrometre resolution deep silicon detector
- 2024
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Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 69:3
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Tidskriftsartikel (refereegranskat)abstract
- Objective. An ultra-fine-pitch deep silicon detector has been developed for clinical photon-counting computed tomography (CT). With a small pixel size of 14 × 650 μm2, it has shown potential to reach micrometre spatial resolution in previous simulation studies. A detector prototype with such geometry has been manufactured, and we report on the first experimental evaluation of its count-rate performance. Approach. The measurement was carried out at MAX IV synchrotron laboratory with 35 keV monochromatic x-rays. By inserting tungsten attenuators of 50, 75, 100, 150, 200, 225, 325 μ m-thicknesses into the beam, the response of the detector to fluence rates from 3.3 × 107 to 1.3 × 1011 mm−2 s−1 was characterized. Main results. The measurement result showed that the detector exhibited count rate linearity up to 6.66 × 108 mm−2 s−1 with 13% count loss and was still functional at count rate up to 2.9 × 1010 mm−2 s−1. A semi-nonparalyzable dead-time model was fitted to the count-rate behaviour of the detector, showing great agreement with the measured data, with an estimated nonparalyzable dead time of 2.9 ns. Significance. This is the first experimental evaluation of the count-rate performance for a deep silicon detector with such small pixel geometry. The results suggest that this type of detector shows the potential to be used at fluence rates encountered in clinical CT with little count loss due to pile-up.
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| 4. |
- Cabo Rios, Alberto, 1990, et al.
(författare)
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Analytical models for initial and intermediate stages of sintering of additively manufactured stainless steel
- 2023
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Ingår i: Acta Materialia. - : Elsevier BV. - 1359-6454. ; 249
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Tidskriftsartikel (refereegranskat)abstract
- In isotropic pressure-less sintering continuum mechanics models, densification kinetics is driven by the balance between the effective sintering stress and bulk viscosity. In components manufactured by binder jetting (BJ), the green structure created by the arrangement of spherical powder particles during printing is characterized by its high porosity (40–50%). This leads to a wide porosity range for the initial and intermediate sintering stages, where a complex combination of diffusion mechanisms drives matter redistribution through the porous compact. In this paper, a comprehensive analysis of the porosity effect on the resistance to densification of 316L BJ during sintering was performed by avoiding other highly influencing factors like δ-ferrite phase transformation. Different normalized bulk moduli expressions, inspired by Skorohod, Hsueh, and Abouaf sintering models, are used in the framework of the continuum theory of sintering. A new material constants determination algorithm based on the sintering experiments design and non-linear analysis of the model was proposed. This evidenced the critical importance of the experimental data collection for the determination of the required sintering model constants. Accordingly, material shear viscosity and normalized bulk viscosity constants were successfully determined based on dilatometry and grain size experimental data. The bulk moduli proposed comprise physical parameters which depend on the interparticle stress distribution or the initial high reactivity of the BJ compacts. The variation of powder size distribution and/or arrangement would potentially impact the determination of these constants in the normalized bulk moduli.
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| 5. |
- Daniel, Maxime, et al.
(författare)
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Charge collection efficiency of CdTe detectors : Impact of charge collection time and polarisation
- 2023
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Ingår i: Medical Imaging 2023. - : SPIE-Intl Soc Optical Eng.
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Konferensbidrag (refereegranskat)abstract
- Cadmium telluride (CdTe) is one of the materials used in photon-counting detectors for x-ray computed tomography. One challenge with this material is that it is susceptible to polarisation due to holes being trapped in impurities in the material. This can potentially lead to the buildup of bulk charge in the semiconductor, causing decreased charge collection efficiency and degraded energy resolution. In this work, we develop a simulation model of CdTe detectors with polarisation and use it to study the effect of polarisation on the measured energy spectrum for different charge collection times. To this end, we use a theoretical model of charge buildup to find the critical charge in the detector's bulk above which the detector can be considered completely polarised. We then simulate a 320-by-270-by-1600 μm CdTe detector used in CT clinical imaging, for varying degrees of polarisation (ratio between the actual charge and the critical charge) and charge collection time. Our results show that the measured spectrum gets heavily distorted for large degrees of polarisation or for short charge collection time. We also put these results in context by discussing how they relate to the critical fluence rate and the time of flight of the charge carriers. These results can lead to improved simulation models of CdTe detectors and a better understanding the factors affecting their imaging performance.
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| 6. |
- Eguizabal, Alma, et al.
(författare)
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Model-based deep learning to achieve interpretable spectral CT denoising
- 2023
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Ingår i: Medical Imaging 2023: Physics of Medical Imaging. - : SPIE-Intl Soc Optical Eng.
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Konferensbidrag (refereegranskat)abstract
- Photon-counting detectors are greatly improving the resolution and image quality in computed tomography (CT) technology. The drawback is, however, that the reconstruction becomes more challenging. This is because there is a considerable increment of the processing data due to the multiple energy bins and materials in the reconstruction analysis, as well as improved resolution. Yet efficient material decomposition and reconstruction methods tend to generate noisy images that do not completely satisfy the expected image quality. Therefore, there is a need for efficient denoising of the resulting material images. We present a new and fast denoiser that is based on a linear minimum mean square error (LMMSE) estimator. The LMMSE is very fast to compute, but not commonly used for CT image denoising, probably due to its inability to adapt the amount of denoising to different parts of the image and the difficulty to derive accurate statistical properties from the CT data. To overcome these problems we propose a model-based deep learning strategy, that is, a deep neural network that preserves an LMMSE structure (model-based), providing more robustness unseen data, as well as good interpretability to the result. In this way, the solution adapts to the anatomy in every point of the image and noise properties at that particular location. In order to asses the performance of the new method, we compare it to both to a conventional LMMSE estimator and to a "black-box"CNN in a simulation study with anthropomorphic phantoms.
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| 7. |
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| 8. |
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Författningssamling för svensk juridik
- 2023
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Denna författningssamling innehåller lagar och förordningar, enligt lydelse den 1 augusti 2017, för att tillse behovet av lagtext på introduktionskurser och översiktskurser i juridik. Vissa lagar återges endast i utdrag för att bibehålla lättillgängligheten.Boken är primärt framtagen för att användas tillsammans med läroboken "Svensk juridik", men kan med fördel även användas med andra läroböcker.
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| 9. |
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| 10. |
- Hein, Dennis, et al.
(författare)
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Spectral CT denoising using a conditional Wasserstein generative adversarial network
- 2023
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Ingår i: Medical Imaging 2023. - : SPIE-Intl Soc Optical Eng.
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Konferensbidrag (refereegranskat)abstract
- Next generation X-ray computed tomography, based on photon-counting detectors, is now clinically available. These new detectors come with the promise of higher contrast-to-noise ratio and spatial resolution and improved low-dose imaging. However, the multi-bin nature of photon-counting detectors renders the image reconstruction problem more difficult. Common approaches, such as the two-step projection-based approach, may result in material basis images with an excessive degree of noise, which limits the clinical usefulness of the images. One possible solution is to "assist"the conventional image reconstruction by post-processing the reconstructed images using deep learning. Such networks are often trained using some pixel-wise loss, such as the mean squared error. This low-level per-pixel comparison is known to lead to over-smoothing and a loss of fine-grained details that are important to the perceptual quality and clinical usefulness of the image. In this abstract, we propose to tackle this issue by including an adversarial loss based on the Wasserstein generative adversarial network with gradient penalty. The adversarial loss will encourage the distribution of the processed images to be similar to that of the ground truth. This helps prevent over-smoothing and ensures that the ground truth texture is well preserved. In particular, we train a version of the UNet using a combination of the mean absolute error and an adversarial loss to correct for noise in the material basis images. We demonstrate that the proposed method can produce denoised virtual monoenergetic images, with realistic texture, at a range of energy levels.
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