Enhancement and segmentation of medical images through pythagorean fuzzy sets-An innovative approach

Image segmentation has attracted a lot of attention due to its potential biomedical applications. Based on these, in the current research, an attempt has been made to explore object enhancement and segmentation for CT images of lungs infected with COVID-19. By implementing Pythagorean fuzzy entropy, the considered images were enhanced. Further, by constructing Pythagorean fuzzy measures and utilizing the thresholding technique, the required values of thresholds for the segmentation of the proposed scheme are assessed. The object extraction ability of the five segmentation algorithms including current sophisticated, and proposed schemes are evaluated by applying the quality measurement factors. Ultimately, the proposed scheme has the best effect on object separation as well as the quality measurement values.

Automated summary

The current research explores object enhancement and segmentation for CT images of lungs infected with COVID-19 using Pythagorean fuzzy entropy, measures, and thresholding technique. The proposed scheme shows the best effect on object separation and quality measurement values compared to other segmentation algorithms in terms of object extraction ability.