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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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.

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1.080 Topics available

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977 Locations available

693.932 PEOPLE
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Naji, M.
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Vercauteren, Tom

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University College London

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2022Enhanced Photoacoustic Visualisation of Clinical Needles by Combining Interstitial and Extracorporeal Illumination of Elastomeric Nanocomposite Coatings7citations
  • 2022Automated Koos Classification of Vestibular Schwannoma12citations
  • 2022Hybrid confocal Raman endomicroscopy for morpho-chemical tissue characterization2citations
  • 2021Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction15citations

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Chart of shared publication
Sathasivam, Sanjayan
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Noimark, Sacha
1 / 4 shared
Collier, Paul
1 / 2 shared
Xia, Wenfeng
1 / 5 shared
Bodian, Semyon
1 / 2 shared
West, Simeon J.
1 / 3 shared
Desjardins, Adrien E.
1 / 4 shared
Gordon, Ross J.
1 / 2 shared
Shi, Mengjie
1 / 1 shared
Paddick, Ian
1 / 1 shared
Ourselin, Sebastien
2 / 10 shared
Kitchen, Neil
1 / 1 shared
Shapey, Jonathan
2 / 2 shared
Kujawa, Aaron
1 / 1 shared
Okasha, Mohamed
1 / 2 shared
Connor, Steve
1 / 1 shared
Oviedova, Anna
1 / 1 shared
Grishchuk, Diana
1 / 1 shared
Jensen, Magnus
1 / 1 shared
Horgan, Conor C.
1 / 1 shared
Cook, Richard
1 / 6 shared
Bergholt, Mads Sylvest
1 / 1 shared
Chiappini, Ciro
1 / 3 shared
Li, Peichao
1 / 1 shared
Horgan, Conor
1 / 1 shared
Bahl, Anisha
1 / 1 shared
Ebner, Michael
1 / 1 shared
Noonan, Philip
1 / 1 shared
Chart of publication period
2022
2021

Co-Authors (by relevance)

  • Sathasivam, Sanjayan
  • Noimark, Sacha
  • Collier, Paul
  • Xia, Wenfeng
  • Bodian, Semyon
  • West, Simeon J.
  • Desjardins, Adrien E.
  • Gordon, Ross J.
  • Shi, Mengjie
  • Paddick, Ian
  • Ourselin, Sebastien
  • Kitchen, Neil
  • Shapey, Jonathan
  • Kujawa, Aaron
  • Okasha, Mohamed
  • Connor, Steve
  • Oviedova, Anna
  • Grishchuk, Diana
  • Jensen, Magnus
  • Horgan, Conor C.
  • Cook, Richard
  • Bergholt, Mads Sylvest
  • Chiappini, Ciro
  • Li, Peichao
  • Horgan, Conor
  • Bahl, Anisha
  • Ebner, Michael
  • Noonan, Philip
OrganizationsLocationPeople

article

Hybrid confocal Raman endomicroscopy for morpho-chemical tissue characterization

  • Jensen, Magnus
  • Horgan, Conor C.
  • Vercauteren, Tom
  • Cook, Richard
  • Bergholt, Mads Sylvest
  • Chiappini, Ciro
Abstract

Confocal laser endomicroscopy (CLE) offers imaging of tissue microarchitecture and has emerged as a promising tool for in vivo clinical diagnosis of cancer across many organs. CLE, however, can show high inter-observer dependency and does not provide information about tissue molecular composition. In contrast, Raman spectroscopy is a label-free optical technique that provides detailed biomolecular compositional information but offers limited or no morphological information. Here we present a novel hybrid fiber-optic confocal Raman endomicroscopy system for morpho-chemical tissue imaging and analysis. The developed confocal endomicroscopy system is based on a novel detection scheme for rejecting Raman silica fiber interference permitting simultaneous CLE imaging and Raman spectral acquisition of tissues through a coherent fiber bundle. We show that this technique enables real-time microscopic visualization of tissue architecture as well as simultaneous pointwise label-free biomolecular characterization and fingerprinting of tissue paving the way for multimodal diagnostics at endoscopy.

Topics
  • impedance spectroscopy
  • Raman spectroscopy