Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients
In this paper, we propose to quantitatively compare the loss of human lung health under the influence of the illness with COVID-19, based on the fractal-analysis interpretation of the chest-pulmonary CT pictures, in the case of small datasets, which are usually encountered in medical applications. T...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Fractal and Fractional |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3110/7/4/285 |
| _version_ | 1797605386432282624 |
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| author | Maria-Alexandra Paun Paraschiva Postolache Mihai-Virgil Nichita Vladimir-Alexandru Paun Viorel-Puiu Paun |
| author_facet | Maria-Alexandra Paun Paraschiva Postolache Mihai-Virgil Nichita Vladimir-Alexandru Paun Viorel-Puiu Paun |
| author_sort | Maria-Alexandra Paun |
| collection | DOAJ |
| description | In this paper, we propose to quantitatively compare the loss of human lung health under the influence of the illness with COVID-19, based on the fractal-analysis interpretation of the chest-pulmonary CT pictures, in the case of small datasets, which are usually encountered in medical applications. The fractal analysis characteristics, such as fractal dimension and lacunarity measured values, have been utilized as an effective advisor to interpretation of pulmonary CT picture texture. |
| first_indexed | 2024-03-11T05:00:22Z |
| format | Article |
| id | doaj.art-ac1d1f95e83b4eff923b7833c6a39427 |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-11T05:00:22Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-ac1d1f95e83b4eff923b7833c6a394272023-11-17T19:19:00ZengMDPI AGFractal and Fractional2504-31102023-03-017428510.3390/fractalfract7040285Fractal Analysis in Pulmonary CT Images of COVID-19-Infected PatientsMaria-Alexandra Paun0Paraschiva Postolache1Mihai-Virgil Nichita2Vladimir-Alexandru Paun3Viorel-Puiu Paun4School of Engineering, Swiss Federal Institute of Technology (EPFL), 1015 Lausanne, SwitzerlandMedical Department, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, RomaniaDoctoral School, Faculty of Applied Sciences, University Politehnica of Bucharest, 060042 Bucharest, RomaniaFive Rescue Research Laboratory, 75004 Paris, FranceDepartment of Physics, Faculty of Applied Sciences, University Politehnica of Bucharest, 060042 Bucharest, RomaniaIn this paper, we propose to quantitatively compare the loss of human lung health under the influence of the illness with COVID-19, based on the fractal-analysis interpretation of the chest-pulmonary CT pictures, in the case of small datasets, which are usually encountered in medical applications. The fractal analysis characteristics, such as fractal dimension and lacunarity measured values, have been utilized as an effective advisor to interpretation of pulmonary CT picture texture.https://www.mdpi.com/2504-3110/7/4/285computed tomographypicture texturefractal analysisfractal dimensionlacunarity |
| spellingShingle | Maria-Alexandra Paun Paraschiva Postolache Mihai-Virgil Nichita Vladimir-Alexandru Paun Viorel-Puiu Paun Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients Fractal and Fractional computed tomography picture texture fractal analysis fractal dimension lacunarity |
| title | Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients |
| title_full | Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients |
| title_fullStr | Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients |
| title_full_unstemmed | Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients |
| title_short | Fractal Analysis in Pulmonary CT Images of COVID-19-Infected Patients |
| title_sort | fractal analysis in pulmonary ct images of covid 19 infected patients |
| topic | computed tomography picture texture fractal analysis fractal dimension lacunarity |
| url | https://www.mdpi.com/2504-3110/7/4/285 |
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