COVID-19 lesion segmentation using lung CT scan images: Comparative study based on active contour models
المؤلف | Akbari Y. |
المؤلف | Hassen H. |
المؤلف | Al-Maadeed, Somaya |
المؤلف | Zughaier S.M. |
تاريخ الإتاحة | 2022-05-19T10:23:07Z |
تاريخ النشر | 2021 |
اسم المنشور | Applied Sciences (Switzerland) |
المصدر | Scopus |
المعرّف | http://dx.doi.org/10.3390/app11178039 |
الملخص | Pneumonia is a lung infection that threatens all age groups. In this paper, we use CT scans to investigate the effectiveness of active contour models (ACMs) for segmentation of pneumonia caused by the Coronavirus disease (COVID-19) as one of the successful methods for image segmentation. A comparison has been made between the performances of the state-of-the-art methods performed based on a database of lung CT scan images. This review helps the reader to identify starting points for research in the field of active contour models on COVID-19, which is a high priority for researchers and practitioners. Finally, the experimental results indicate that active contour methods achieve promising results when there are not enough images to use deep learning-based methods as one of the powerful tools for image segmentation. |
راعي المشروع | Funding: This research was funded by Qatar University Emergency Response Grant (QUERG-CENG-2020-1) from Qatar University. |
اللغة | en |
الناشر | MDPI |
الموضوع | Active contour models Chest CT scans COVID-19 infection Edge-based models Level set methods Parametric methods Pneumonia Region-based models |
النوع | Article |
رقم العدد | 17 |
رقم المجلد | 11 |
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