| Autor: |
Malavika.V. Nair, R. Rakshana, Venkatesan Rajinikanth, C.N. Gnanaprakasam, N. Keerthana |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
2018 International Conference on Recent Trends in Advance Computing (ICRTAC). |
| DOI: |
10.1109/icrtac.2018.8679193 |
| Popis: |
Breast-Cancer (BC) is a life intimidating illness among the women society and early revealing may assist to afford suitable treatment to reduce risk factor. Digital-Mammogram (DM) is an accepted practice to record and inspect BC. The work presented here implements a Hybrid Image-Processing-Tool by combining Tsallis-Thresholding (TT) and Level-Set-Segmentation (LSS). This tool helps to mine the apprehensive division of DM. Primarily, Jaya-Algorithm based TT using three-stage thresholding is executed to enhance the DM and later, the LSS is considered to mine the infected section. The mined region is then assessed with the GLCM to know the harshness of infection by investigating its texture-features. The investigational outcome of this paper authenticates the superiority of proposed tool in extracting the breast melanoma from the chosen DM dataset. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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