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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Diagnostics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4418/12/12/3208 |
| _version_ | 1797460632076812288 |
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| author | Aleksandar Simović Maja Lutovac-Banduka Snežana Lekić Valentin Kuleto |
| author_facet | Aleksandar Simović Maja Lutovac-Banduka Snežana Lekić Valentin Kuleto |
| author_sort | Aleksandar Simović |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T17:08:46Z |
| format | Article |
| id | doaj.art-d66fee7547aa41d29fe0b40ccfe72386 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T17:08:46Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-d66fee7547aa41d29fe0b40ccfe723862023-11-24T14:20:37ZengMDPI AGDiagnostics2075-44182022-12-011212320810.3390/diagnostics12123208Smart Visualization of Medical Images as a Tool in the Function of Education in NeuroradiologyAleksandar Simović0Maja Lutovac-Banduka1Snežana Lekić2Valentin Kuleto3Department of Information Technology, Information Technology School ITS, 11000 Belgrade, SerbiaDepartment of RT-RK Institute, RT-RK for Computer Based Systems, 21000 Novi Sad, SerbiaDepartment of Emergency Neuroradiology, University Clinical Centre of Serbia UKCS, 11000 Belgrade, SerbiaDepartment of Information Technology, Information Technology School ITS, 11000 Belgrade, SerbiaThe 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.https://www.mdpi.com/2075-4418/12/12/3208smart visualizationmedical imagingSVMIneuroradiologyeducation |
| spellingShingle | Aleksandar Simović Maja Lutovac-Banduka Snežana Lekić Valentin Kuleto Smart Visualization of Medical Images as a Tool in the Function of Education in Neuroradiology Diagnostics smart visualization medical imaging SVMI neuroradiology education |
| 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 | smart visualization medical imaging SVMI neuroradiology education |
| url | https://www.mdpi.com/2075-4418/12/12/3208 |
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