![]() Because image interpretation is operator-dependent and requires skill, information technology is required to speed up and improve the accuracy of diagnosis while also offering a second opinion to the expert 21. These modalities create images that have lowered mortality rates by 30–70% 20 as a technique of assisting radiologists and clinicians in recognising problems. Digital mammography 4, 5, ultrasound 6, magnetic resonance imaging 7, 8, 9, 10, 11, 12, 13, 14, 15, 97, 17, 18, microscopic slices, and infrared thermogram 19 are some of the medical imaging modalities used for diagnosis. Medical imaging testing is the most effective method for detecting breast cancer 3. If global mortality rates decreased by 2.5 percent annually between 20, 2.5 million breast cancer deaths might be avoided.įurthermore, in rural regions, a scarcity of medical specialists and experts exacerbates the difficulty of early and accurate breast cancer diagnosis, leading to a higher mortality rate. In nations that have been successful in lowering it, the annual mortality rate from breast cancer has fallen by 2-4 percent. Breast cancer survival rates range from 40 percent in South Africa and 66 percent in India to more than 90 percent in high-income nations five years after diagnosis. In high-income nations, early diagnosis and treatment have been demonstrated to be beneficial, and it should be done in low-income countries with minimal equipment. ![]() “As of the end of 2020, there were 7.8 million women alive who were diagnosed with breast cancer in the past 5 years, making it the world’s most prevalent cancer” 2. In 2020 breast cancer was being diagnosed in worldwide 2.3 million women, with 685,000 deaths owing to the disease. In comparison to developed countries, mortality rates in low and middle-income countries are comparatively high. According to both quantitative and qualitative findings, the proposed strategies outperform other compared methodologies.īreast cancer in women is one of the most frequent cancers worldwide 1, and it is the main reason why women die. Furthermore, Multi-Criteria Decision Making is used to evaluate overall performance focused on sensitivity, accuracy, false-positive rate, precision, specificity, \(F_1\)-score, Geometric-Mean, and DSC. The one-way ANOVA test followed by Tukey HSD and Wilcoxon Signed Rank Test are used to examine the results. Another proposed GTORBL-based segmentation method achieves accuracy values of \(99.31\%\), sensitivity of \(95.45\%\), and DSC of \(91.54\%\). ![]() The Dice Similarity Coefficient (DSC), sensitivity, and accuracy of the proposed GTO-based approach is achieved \(87.04\%\), \(90.96\%\), and \(98.13\%\) respectively. The proposed approaches are compared with Tunicate Swarm Algorithm (TSA), Particle Swarm Optimization (PSO), Arithmetic Optimization Algorithm (AOA), Slime Mould Algorithm (SMA), Multi-verse Optimization (MVO), Hidden Markov Random Field (HMRF), Improved Markov Random Field (IMRF), and Conventional Markov Random Field (CMRF). The proposed approaches are tested on 20 patients’ T2 Weighted Sagittal (T2 WS) DCE-MRI 100 slices. An improved GTO, is developed by incorporating Rotational opposition based-learning (RBL) into GTO called (GTORBL) and applied it to the same problem. Kapur’s entropy-based multilevel thresholding is used in this study to determine optimal values for breast DCE-MRI lesion segmentation using Gorilla Troops Optimization (GTO). ![]() The Magnetic Resonance Imaging (MRI) segmentation techniques for breast cancer diagnosis are investigated in this article. Early detection and treatment of breast cancer are thought to reduce the need for surgery and boost the survival rate. Breast cancer has emerged as the most life-threatening disease among women around the world. ![]()
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