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Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology
The smart visualization of medical images (SVMI) model is based on multi-detector computed tomography (MDCT) data sets and can provide a clearer view of changes in the brain, such as tumors (expansive changes), bleeding, and ischemia on native imaging (i.e., a non-contrast MDCT scan). The new SVMI m...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777748/ https://www.ncbi.nlm.nih.gov/pubmed/36553215 http://dx.doi.org/10.3390/diagnostics12123208 |
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author | Simović, Aleksandar Lutovac-Banduka, Maja Lekić, Snežana Kuleto, Valentin |
author_facet | Simović, Aleksandar Lutovac-Banduka, Maja Lekić, Snežana Kuleto, Valentin |
author_sort | Simović, Aleksandar |
collection | PubMed |
description | The smart visualization of medical images (SVMI) model is based on multi-detector computed tomography (MDCT) data sets and can provide a clearer view of changes in the brain, such as tumors (expansive changes), bleeding, and ischemia on native imaging (i.e., a non-contrast MDCT scan). The new SVMI method provides a more precise representation of the brain image by hiding pixels that are not carrying information and rescaling and coloring the range of pixels essential for detecting and visualizing the disease. In addition, SVMI can be used to avoid the additional exposure of patients to ionizing radiation, which can lead to the occurrence of allergic reactions due to the contrast media administration. Results of the SVMI model were compared with the final diagnosis of the disease after additional diagnostics and confirmation by neuroradiologists, who are highly trained physicians with many years of experience. The application of the realized and presented SVMI model can optimize the engagement of material, medical, and human resources and has the potential for general application in medical training, education, and clinical research. |
format | Online Article Text |
id | pubmed-9777748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97777482022-12-23 Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology Simović, Aleksandar Lutovac-Banduka, Maja Lekić, Snežana Kuleto, Valentin Diagnostics (Basel) Article The smart visualization of medical images (SVMI) model is based on multi-detector computed tomography (MDCT) data sets and can provide a clearer view of changes in the brain, such as tumors (expansive changes), bleeding, and ischemia on native imaging (i.e., a non-contrast MDCT scan). The new SVMI method provides a more precise representation of the brain image by hiding pixels that are not carrying information and rescaling and coloring the range of pixels essential for detecting and visualizing the disease. In addition, SVMI can be used to avoid the additional exposure of patients to ionizing radiation, which can lead to the occurrence of allergic reactions due to the contrast media administration. Results of the SVMI model were compared with the final diagnosis of the disease after additional diagnostics and confirmation by neuroradiologists, who are highly trained physicians with many years of experience. The application of the realized and presented SVMI model can optimize the engagement of material, medical, and human resources and has the potential for general application in medical training, education, and clinical research. MDPI 2022-12-17 /pmc/articles/PMC9777748/ /pubmed/36553215 http://dx.doi.org/10.3390/diagnostics12123208 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Simović, Aleksandar Lutovac-Banduka, Maja Lekić, Snežana Kuleto, Valentin Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title | Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title_full | Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title_fullStr | Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title_full_unstemmed | Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title_short | Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology |
title_sort | smart visualization of medical images as a tool in the function of education in neuroradiology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9777748/ https://www.ncbi.nlm.nih.gov/pubmed/36553215 http://dx.doi.org/10.3390/diagnostics12123208 |
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