Materials Map

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

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

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.

×

Materials Map under construction

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.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Harms, J.

  • Google
  • 1
  • 9
  • 3

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2022A component method to delineate surgical spine implants for proton Monte Carlo dose calculation.3citations

Places of action

Chart of shared publication
Slopsema, R.
1 / 1 shared
Yoon, T.
1 / 1 shared
Mw, Mcdonald
1 / 1 shared
Refai, D.
1 / 1 shared
Jd, Bradley
1 / 1 shared
Wolf, J.
1 / 13 shared
Zhou, J.
1 / 38 shared
Leng, S.
1 / 1 shared
Charyyev, Serdar
1 / 1 shared
Chart of publication period
2022

Co-Authors (by relevance)

  • Slopsema, R.
  • Yoon, T.
  • Mw, Mcdonald
  • Refai, D.
  • Jd, Bradley
  • Wolf, J.
  • Zhou, J.
  • Leng, S.
  • Charyyev, Serdar
OrganizationsLocationPeople

article

A component method to delineate surgical spine implants for proton Monte Carlo dose calculation.

  • Harms, J.
  • Slopsema, R.
  • Yoon, T.
  • Mw, Mcdonald
  • Refai, D.
  • Jd, Bradley
  • Wolf, J.
  • Zhou, J.
  • Leng, S.
  • Charyyev, Serdar
Abstract

<h4>Purpose</h4>Metallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images.<h4>Methods</h4>The proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours.<h4>Results</h4>For in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm<sup>3</sup> for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm<sup>3</sup> , respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm<sup>3</sup> for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt-chromium alloys by different vendors.<h4>Conclusions</h4>A component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof-of-concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head-and-neck patients where tight margins are required to spare organs at risk.

Topics
  • impedance spectroscopy
  • chromium
  • tomography
  • titanium
  • cobalt
  • dosimetry
  • chromium alloy