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1000 Titel
  • Automatic segmentation and volumetric assessment of internal organs and fatty tissue: what are the benefits?
1000 Autor/in
  1. Schick, Fritz |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-12-17
1000 Erschienen in
1000 Quellenangabe
  • 35(2):187-192
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s10334-021-00986-1 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995273/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Objective!#!This study presents the development and evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment that can be applied to improve the testing procedure for MR image artifacts in medical implants according to ASTM F2119.!##!Methods!#!The numerical approach is validated by comparing simulations and measurements of two metallic test objects made of titanium and stainless steel at three different field strengths (1.5T, 3T and 7T). The difference in artifact size and shape between the simulated and measured artifacts were evaluated. A trend analysis of the artifact sizes in relation to the field strength was performed.!##!Results!#!The numerical simulation approach shows high similarity (between 75% and 84%) of simulated and measured artifact sizes of metallic implants. Simulated and measured artifact sizes in relation to the field strength resulted in a calculation guideline to determine and predict the artifact size at one field strength (e.g., 3T or 7T) based on a measurement that was obtained at another field strength only (e.g. 1.5T).!##!Conclusion!#!This work presents a novel tool to improve the MR image artifact testing procedure of passive medical implants. With the help of this tool detailed artifact investigations can be performed, which would otherwise only be possible with substantial measurement effort on different MRI systems and field strengths.
1000 Sacherschließung
lokal Solid State Physics
lokal Tomography, X-Ray Computed [MeSH]
lokal Biomedical Engineering and Bioengineering
lokal Basic Science - Image analysis
lokal Image Processing, Computer-Assisted [MeSH]
lokal Imaging / Radiology
lokal Health Informatics
lokal Commentary
lokal Computer Appl. in Life Sciences
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-4231-3406
1000 Hinweis
  • DeepGreen-ID: 41050ec985774633aba06f3428f2b4ef ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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1000 Dateien
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1000 @id frl:6448827.rdf
1000 Erstellt am 2023-05-04T10:28:45.114+0200
1000 Erstellt von 322
1000 beschreibt frl:6448827
1000 Zuletzt bearbeitet Fri Oct 13 17:04:09 CEST 2023
1000 Objekt bearb. Fri Oct 13 17:04:09 CEST 2023
1000 Vgl. frl:6448827
1000 Oai Id
  1. oai:frl.publisso.de:frl:6448827 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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