Abstract
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.
Highlights
The new 2019 coronavirus, named COVID-19 by the World Health Organization (WHO), is attracting a lot of attention lately because it is a new type of coronavirus that is highly contagious and has not been seen in humans before [1]
Since our goal is to investigate the effectiveness of active contouring methods for segmenting COVID-19 infected regions from the CTSI, current methods for segmenting COVID-19 pneumonia using the CTSI are examined below
This paper deals with CT COVID-19 image segmentation
Summary
The new 2019 coronavirus, named COVID-19 by the World Health Organization (WHO), is attracting a lot of attention lately because it is a new type of coronavirus that is highly contagious and has not been seen in humans before [1]. Due to the lower sensitivity of some tests leading to false-negative results, other methods may be considered to aid in COVID-19 diagnosis. To facilitate COVID-19 diagnosis, medical radiological imaging is used as a valuable supplemental diagnostic tool to evaluate the infectious process. Radiologic imaging such as radiographs is usually performed in patients with clinical symptoms suggestive of pulmonary infection [1]. The energy functional is a function of contour’s internal energy (Eint) addition to the external energy (Eext). These energies are two functions of the set of points (x(s), y(s)), which make up a snake c(s) = (x(s), y(s)).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
