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- W4312636666 abstract "Breast cancer is recognized as one of the biggest current challenges impacting the lives of thousands of women around the world. An early diagnosis based on the study of mammogram is one of the most powerful methods to prevent this disease. Segmenting images or extracting object boundaries is one of the major computer vision and image processing issues. Active contours are used widely for segmentation as a high-level technology for boundary recognition. Chan-Vese was used as a method for segmenting i.e., geometric active contours. This method is particularly powerful when dealing with homogeneous images, Therefore, she has difficulty segmenting the mammogram images because It lacks contrast between the tumour and the surrounding breast tissue. Work was done to increase the contrast through pre-processing where he used CLAHE to improve the mammogram images and thus help Chan-Vese to define the tumour boundaries. The method was tested on the MIAS mini database, and the highest quantitative results were as follows (0.88, 0.94, 0.99, 0.98, 0.99) for Jaccard, Dice, PF-Score, Precision, and Sensitivity respectively." @default.
- W4312636666 created "2023-01-05" @default.
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- W4312636666 date "2022-01-01" @default.
- W4312636666 modified "2023-10-15" @default.
- W4312636666 title "Segmentation of breast mammogram images using level set method" @default.
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- W4312636666 doi "https://doi.org/10.1063/5.0093693" @default.
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