Abstract
Breast cancer is the second leading cause of death among a large number of women worldwide. It may be challenging for radiologists to diagnose and treat breast cancer. Consequently, primary care improves disease prevention and death. Early detection increases treatment options and saves life, which is the major target of this research. This research indicates the versatility of the methodology by integrating contemporary segmentation approaches with machine learning methods, which are developing areas of research. In the pre-processing process, an adaptive median filter is utilized for noise removal, enhancement of image quality, conservation of edges, and smoothing. This research makes a significant contribution by proposing a new parameter for evaluating K-means and a Gaussian mixture model (GMM) performance. A hybrid combination of segmentation and detection was applied to breast cancer. The proposed technique is significant for classifying benign and malignant tumors. The simulated results are discussed and evaluated to determine the competence of this method for the early diagnosis of breast cancer. This method allows medical experts to recognize breast cancer at a faster rate and provide higher accuracy. An ANOVA test was used to determine the multi-variant analysis and prediction rate for the proposed method.
Highlights
Experts in modern medical areas are focusing more on technical approaches for a variety of chronic diseases
It is proven that the hybrid approach has better performance measures, such as an accuracy of 95.5%, an error rate of 18.64%, and a signal-tonoise of 13.05 when compared to other existing techniques
The Analysis of variance (ANOVA) test checks the impact of one or more factors by comparing the mean, variances, and standard deviations of different samples. It shows a high prediction rate for the hybrid segmentation technique used in breast cancer detection
Summary
Experts in modern medical areas are focusing more on technical approaches for a variety of chronic diseases. According to a statistical report on medical health, cancer is a genetic disease that leads to variations in genes involved in the functionality of human body cells. Variation of the gene in genetic diseases may affect the internal parts of human organs for future generations. It may affect DNA structure, resulting in environmental exposure to substances such as UV radiation, smoking, and other variables that are significant in the development of breast cancer [1]. 60% of women affected by breast cancer are diagnosed at the last stage, which leads to death in women
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