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المؤلفAkbari Y.
المؤلفHassen H.
المؤلفAl-Maadeed, Somaya
المؤلفZughaier S.M.
تاريخ الإتاحة2022-05-19T10:23:07Z
تاريخ النشر2021
اسم المنشورApplied Sciences (Switzerland)
المصدرScopus
المعرّفhttp://dx.doi.org/10.3390/app11178039
معرّف المصادر الموحدhttp://hdl.handle.net/10576/31086
الملخصPneumonia 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 المشروعFunding: This research was funded by Qatar University Emergency Response Grant (QUERG-CENG-2020-1) from Qatar University.
اللغةen
الناشرMDPI
الموضوعActive contour models
Chest CT scans
COVID-19 infection
Edge-based models
Level set methods
Parametric methods
Pneumonia
Region-based models
العنوانCOVID-19 lesion segmentation using lung CT scan images: Comparative study based on active contour models
النوعArticle
رقم العدد17
رقم المجلد11
dc.accessType Abstract Only


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