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Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries

Computer simulations provide virtual hands-on experience when actual hands-on experience is not possible. To use these simulations in medical science, they need to be able to predict the behavior of actual processes with actual patient-specific geometries. Many uncertainties enter in the process of...

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Detalles Bibliográficos
Autores principales: Toma, M., Lu, Y., Zhou, H., Garcia, J. D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shiraz University of Medical Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859371/
https://www.ncbi.nlm.nih.gov/pubmed/33564647
http://dx.doi.org/10.31661/jbpe.v0i0.2001-1062
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author Toma, M.
Lu, Y.
Zhou, H.
Garcia, J. D.
author_facet Toma, M.
Lu, Y.
Zhou, H.
Garcia, J. D.
author_sort Toma, M.
collection PubMed
description Computer simulations provide virtual hands-on experience when actual hands-on experience is not possible. To use these simulations in medical science, they need to be able to predict the behavior of actual processes with actual patient-specific geometries. Many uncertainties enter in the process of developing these simulations, starting with creating the geometry. The actual patient-specific geometry is often complex and hard to process. Usually, simplifications to the geometry are introduced in exchange for faster results. However, when simplified, these simulations can no longer be considered patient-specific as they do not represent the actual patient they come from. The ultimate goal is to keep the geometries truly patient-specific without any simplification. However, even without simplifications, the patient-specific geometries are based on medical imaging modalities and consequent use of numerical algorithms to create and process the 3D surface. Multiple users are asked to process medical images of a complex geometry. Their resulting geometries are used to assess how the user’s choices determine the resulting dimensions of the 3D model. It is shown that the resulting geometry heavily depends on user’s choices.
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spelling pubmed-78593712021-02-08 Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries Toma, M. Lu, Y. Zhou, H. Garcia, J. D. J Biomed Phys Eng Technical Note Computer simulations provide virtual hands-on experience when actual hands-on experience is not possible. To use these simulations in medical science, they need to be able to predict the behavior of actual processes with actual patient-specific geometries. Many uncertainties enter in the process of developing these simulations, starting with creating the geometry. The actual patient-specific geometry is often complex and hard to process. Usually, simplifications to the geometry are introduced in exchange for faster results. However, when simplified, these simulations can no longer be considered patient-specific as they do not represent the actual patient they come from. The ultimate goal is to keep the geometries truly patient-specific without any simplification. However, even without simplifications, the patient-specific geometries are based on medical imaging modalities and consequent use of numerical algorithms to create and process the 3D surface. Multiple users are asked to process medical images of a complex geometry. Their resulting geometries are used to assess how the user’s choices determine the resulting dimensions of the 3D model. It is shown that the resulting geometry heavily depends on user’s choices. Shiraz University of Medical Sciences 2021-02-01 /pmc/articles/PMC7859371/ /pubmed/33564647 http://dx.doi.org/10.31661/jbpe.v0i0.2001-1062 Text en Copyright: © Journal of Biomedical Physics and Engineering http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License, ( http://creativecommons.org/licenses/by-nc/4.0/ ) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Note
Toma, M.
Lu, Y.
Zhou, H.
Garcia, J. D.
Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title_full Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title_fullStr Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title_full_unstemmed Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title_short Thresholding Segmentation Errors and Uncertainty with Patient-Specific Geometries
title_sort thresholding segmentation errors and uncertainty with patient-specific geometries
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859371/
https://www.ncbi.nlm.nih.gov/pubmed/33564647
http://dx.doi.org/10.31661/jbpe.v0i0.2001-1062
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