Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (5/5 displayed)

  • 2023Contrast-enhanced ultrasound imaging using capacitive micromachined ultrasonic transducers4citations
  • 2022A Hand-Held 190+190 Row–Column Addressed CMUT Probe for Volumetric Imaging5citations
  • 20213D printed calibration micro-phantoms for super-resolution ultrasound imaging validation24citations
  • 2020Micromachined 2D Transducers and Phantoms for 3D Super-Resolution Ultrasound Imagingcitations
  • 20193D Printed Calibration Micro-phantoms for Validation of Super-Resolution Ultrasound Imaging2citations

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Tomov, Borislav Gueorguiev
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Øygard, Sigrid Husebø
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Thomsen, Erik Vilain
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Jensen, Jørgen Arendt
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Stuart, Matthias Bo
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Larsen, Niels Bent
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Diederichsen, Søren Elmin
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Grass, Rune Sixten
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Moesner, Lars N.
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Havreland, Andreas S.
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Bhatti, Mudabbir T.
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Beers, Christopher
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Engholm, Mathias
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Pedersen, Stine Løvholt Grue
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Schou, Mikkel
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Co-Authors (by relevance)

  • Tomov, Borislav Gueorguiev
  • Øygard, Sigrid Husebø
  • Thomsen, Erik Vilain
  • Jensen, Jørgen Arendt
  • Stuart, Matthias Bo
  • Larsen, Niels Bent
  • Diederichsen, Søren Elmin
  • Grass, Rune Sixten
  • Moesner, Lars N.
  • Havreland, Andreas S.
  • Bhatti, Mudabbir T.
  • Beers, Christopher
  • Engholm, Mathias
  • Pedersen, Stine Løvholt Grue
  • Schou, Mikkel
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article

3D printed calibration micro-phantoms for super-resolution ultrasound imaging validation

  • Schou, Mikkel
  • Thomsen, Erik Vilain
  • Jensen, Jørgen Arendt
  • Ommen, Martin Lind
  • Beers, Christopher
  • Larsen, Niels Bent
Abstract

This study evaluates the use of 3D printed phantoms for 3D super-resolution ultrasound imaging (SRI) algorithm calibration. The main benefit of the presented method is the ability to do absolute 3D micro-positioning of sub-wavelength sized ultrasound scatterers in a material having a speed of sound comparable to that of tissue. Stereolithography is used for 3D printing soft material calibration micro-phantoms containing eight randomly placed scatterers of nominal size 205 μm205 μm200 μm. The backscattered pressure spatial distribution is evaluated to show similar distributions from micro-bubbles as the 3D printed scatterers. The printed structures are found through optical validation to expand linearly in all three dimensions by 2.6% after printing. SRI algorithm calibration is demonstrated by imaging a phantom using a /2 pitch 3 MHz 62+62 row-column addressed (RCA) ultrasound probe. The printed scatterers will act as point targets, as their dimensions are below the diffraction limit of the ultrasound system used. Two sets of 640 volumes containing the phantom features are imaged, with an intervolume uni-axial movement of the phantom of 12.5 μm, to˜ emulate a flow velocity of 2 mm/s at a frame rate of 160 Hz. The ultrasound signal is passed to a super-resolution pipeline to localise the positions of the scatterers and track them across the 640 volumes. After compensating for the phantom expansion, a scaling of 0.989 is found between the distance between the eight scatterers calculated from the ultrasound data and the designed distances. The standard deviation of the variation in the scatterer positions along each track is used as an estimate of the precision of the super-resolution algorithm, and is expected to be between the two limiting estimates of (σ<sub><i>x</i>, </sub>σ<sub><i>y</i>, </sub>σ<sub><i>z</i></sub>) = (22.7 μm, 27.6 μm, 9.7 μm) and (σ<sub><i>x</i>, </sub>σ<sub><i>y</i>, </sub>σ<sub><i>z</i></sub>) = (18.7 μm, 19.3 μm, 8.9 μm). In conclusion, this study demonstrates the use of 3D printed phantoms for determining the accuracy and precision of volumetric super-resolution algorithms. 

Topics
  • impedance spectroscopy