Materials Map

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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%

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Publications (1/1 displayed)

  • 2021A novel visualization system of using augmented reality in knee replacement surgery6citations

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Rashid, Tarik A.
1 / 2 shared
Abdullah, Salma
1 / 1 shared
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2021

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  • Rashid, Tarik A.
  • Abdullah, Salma
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article

A novel visualization system of using augmented reality in knee replacement surgery

  • Rashid, Tarik A.
  • Abdullah, Salma
  • Maharjan, Nitish
Abstract

Background and Aim<p>Image registration and alignment are the mainlimitations of augmented reality (AR)-based knee replacement surgery.This research aims to decrease the registration error, eliminateoutcomes that are trapped in local minima to improve the alignmentproblems, handle the occlusion and maximize the overlapping parts.</p>Methodology<p>Markerless image registration method was used forAR-based knee replacement surgery to guide and visualize the surgicaloperation. While weight least square algorithm was used to enhancestereo camera-based tracking by filling border occlusion inright-to-left direction and non-border occlusion from left-to-rightdirection.</p>Results<p>This study has improved video precision to0.57–0.61 mm alignment error. Furthermore, with the use of bidirectionalpoints, that is, forward and backward directional cloud point, theiteration on image registration was decreased. This has led to improvethe processing time as well. The processing time of video frames wasimproved to 7.4–11.74 frames per second.</p>Conclusions<p>It seems clear that this proposed system has focusedon overcoming the misalignment difficulty caused by the movement ofpatient and enhancing the AR visualization during knee replacementsurgery. The proposed system was reliable and favourable which helps ineliminating alignment error by ascertaining the optimal rigidtransformation between two cloud points and removing the outliers andnon-Gaussian noise. The proposed AR system helps in accuratevisualization and navigation of anatomy of knee such as femur, tibia,cartilage, blood vessels and so forth.</p>

Topics
  • impedance spectroscopy