Research about breast cancer consciousness has discovered that social and strict issues imply that ladies don’t get to health administrations, are reluctant to counsel male specialists despite the fact in their relatives particularly couldn’t discuss with husbands also. Breast tumor analysis is rarely simple; it is particularly hard when the lady is in her age of 30’s and has recently begun arranging a future for herself and her family. Hence, a new Meta heuristic Duck traveller optimization algorithm is used to segment the breast tumor to help the doctors to disease diagnosis. Methods: Selecting the best duck from given duck flock is an example of optimization. Optimizing the threshold values VDTO based multilevel thresholding (VDTO-MTH) algorithm is introduced to segmenting the cancer. Desired region of the breast is determined by using VDTO based Region Growing (VDTO-ROI) to highlighting the tumor region. To improving the segmentation results VDTO with K-Means Clustering is proposed (VDTO-K means). Results: The performance results of EDTO are evaluated by using the quality metrics accuracy, precision, recall and f-measure. Conclusion: It is assessed that high mortality because of breast tumor in India would increment throughout the long term. Hence, these calculations discover a terrible requirement for starting essential and auxiliary counteraction measures for the control of breast tumor in our country.
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