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2D Anatomical Structure for COVID-19 Medical Images.
Zimeras, Stelios; Diomidous, Marianna.
  • Zimeras S; Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Samos, Greece.
  • Diomidous M; Department of Nursing, National and Kapodistrian University of Athens, Greece.
Stud Health Technol Inform ; 295: 542-544, 2022 Jun 29.
Article in English | MEDLINE | ID: covidwho-1924044
ABSTRACT
For many clinical goals like surgical planning and radiotherapy treatment planning is necessary to understand the anatomical structures of the organ that is targeted. At the same time the 2D/3D shape of the organ is important to be reconstructed for the benefit of the doctors. For that reason, accurate segmentation techniques must be proposed to overcome the big data medical image storage problem. The main purpose of this work is to apply segmentation techniques for the definition of 3D organs (anatomical structures) when big data information has been stored and must be organized by the doctors for medical diagnosis. The processes would be implemented in the CT images from patients with COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Imaging, Three-Dimensional / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article Affiliation country: SHTI220785

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Imaging, Three-Dimensional / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Stud Health Technol Inform Journal subject: Medical Informatics / Health Services Research Year: 2022 Document Type: Article Affiliation country: SHTI220785