Publication Type : Journal Article
Publisher : Springer Science and Business Media LLC
Source : Neural Computing and Applications
Url : https://doi.org/10.1007/s00521-022-07043-5
Campus : Coimbatore
School : School of Physical Sciences
Department : Mathematics
Year : 2022
Abstract : 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.
Cite this Research Publication : R. Premalatha, P. Dhanalakshmi, Enhancement and segmentation of medical images through pythagorean fuzzy sets-An innovative approach, Neural Computing and Applications, Springer Science and Business Media LLC, 2022, https://doi.org/10.1007/s00521-022-07043-5