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An Improved Fully Automated Breast Cancer Detection and Classification System

Computers, Materials & Continua 2023年第7期76卷 731-751页

作者： Tawfeeq Shawly Ahmed A.Alsheikhy Department of Electrical Engineering Faculty of Engineering at RabighKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityArarSaudi Arabia

More than 500,000 patients are diagnosed with breast cancer *** worldwide reported a death rate of 11.6%in *** tumors are considered a fatal disease and primarily affect middle-aged *** approaches to identify and classify the disease using different technologies,such as deep learning and image segmentation,have been *** of these methods reach 99%***,boosting accuracy remains highly important as patients’lives depend on early diagnosis and specified treatment *** paper presents a fully computerized method to detect and categorize tumor masses in the breast using two deep-learning models and a classifier on different *** method specifically uses ResNet50 and AlexNet,convolutional neural networks(CNNs),for deep learning and a K-Nearest-Neighbor(KNN)algorithm to classify *** experiments have been conducted on five datasets:the Mammographic Image Analysis Society(MIAS),Breast Cancer Histopathological Annotation and Diagnosis(BreCaHAD),King Abdulaziz University Breast Cancer Mammogram Dataset(KAU-BCMD),Breast Histopathology Images(BHI),and Breast Cancer Histopathological Image Classification(BreakHis).These datasets were used to train,validate,and test the presented *** obtained results achieved an average of 99.38%accuracy,surpassing other *** performance quantities,including precision,recall,specificity,and F-score,reached 99.71%,99.46%,98.08%,and 99.67%,*** outcomes indicate that the presented method offers essential aid to pathologists diagnosing breast *** study suggests using the implemented algorithm to support physicians in analyzing breast cancer correctly.

关键词： Breast cancer early detection classification CAD CNN ResNet50 pathology artificial intelligence ifabcics

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