AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis
This work addresses the critical need for the early detection of breast cancer, a significant health concern worldwide. Using a combination of advanced deep learning and machine learning techniques, we offer a comprehensive solution to enhance breast cancer detection accuracy. By leveraging state-of...
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| Format: | Article |
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MDPI AG
2025-03-01
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| Online Access: | https://www.mdpi.com/2078-2489/16/4/278 |
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| author | Amro Moursi Abdulrahman Aboumadi Uvais Qidwai |
| author_facet | Amro Moursi Abdulrahman Aboumadi Uvais Qidwai |
| author_sort | Amro Moursi |
| collection | DOAJ |
| description | This work addresses the critical need for the early detection of breast cancer, a significant health concern worldwide. Using a combination of advanced deep learning and machine learning techniques, we offer a comprehensive solution to enhance breast cancer detection accuracy. By leveraging state-of-the-art convolutional neural networks (CNNs) like GoogLeNet, AlexNet, and ResNet18, alongside traditional classifiers such as k-nearest neighbors (KNN) and support vector machine (SVM), we ensure robust prediction capabilities. Our preprocessing methods significantly improve input data quality, leading to promising detection accuracies. For instance, ResNet-18 achieved impressive results, outperforming other models. Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. This work represents a vital step towards more effective breast cancer diagnosis, underscoring the importance of early intervention for improved patient outcomes. |
| format | Article |
| id | doaj-art-ec697f6cdad1410ea923d4e4310c1e04 |
| institution | OA Journals |
| issn | 2078-2489 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Information |
| spelling | doaj-art-ec697f6cdad1410ea923d4e4310c1e042025-08-20T02:17:59ZengMDPI AGInformation2078-24892025-03-0116427810.3390/info16040278AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image AnalysisAmro Moursi0Abdulrahman Aboumadi1Uvais Qidwai2Department of Computer Science and Engineering, College of Engineering, Qatar University, Doha 2713, QatarDepartment of Computer Science and Engineering, College of Engineering, Qatar University, Doha 2713, QatarDepartment of Computer Science and Engineering, College of Engineering, Qatar University, Doha 2713, QatarThis work addresses the critical need for the early detection of breast cancer, a significant health concern worldwide. Using a combination of advanced deep learning and machine learning techniques, we offer a comprehensive solution to enhance breast cancer detection accuracy. By leveraging state-of-the-art convolutional neural networks (CNNs) like GoogLeNet, AlexNet, and ResNet18, alongside traditional classifiers such as k-nearest neighbors (KNN) and support vector machine (SVM), we ensure robust prediction capabilities. Our preprocessing methods significantly improve input data quality, leading to promising detection accuracies. For instance, ResNet-18 achieved impressive results, outperforming other models. Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. This work represents a vital step towards more effective breast cancer diagnosis, underscoring the importance of early intervention for improved patient outcomes.https://www.mdpi.com/2078-2489/16/4/278ultrasound imagespreprocessingdeep learningmachine learninguser interface |
| spellingShingle | Amro Moursi Abdulrahman Aboumadi Uvais Qidwai AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis Information ultrasound images preprocessing deep learning machine learning user interface |
| title | AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis |
| title_full | AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis |
| title_fullStr | AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis |
| title_full_unstemmed | AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis |
| title_short | AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis |
| title_sort | ai based breast cancer detection system deep learning and machine learning approaches for ultrasound image analysis |
| topic | ultrasound images preprocessing deep learning machine learning user interface |
| url | https://www.mdpi.com/2078-2489/16/4/278 |
| work_keys_str_mv | AT amromoursi aibasedbreastcancerdetectionsystemdeeplearningandmachinelearningapproachesforultrasoundimageanalysis AT abdulrahmanaboumadi aibasedbreastcancerdetectionsystemdeeplearningandmachinelearningapproachesforultrasoundimageanalysis AT uvaisqidwai aibasedbreastcancerdetectionsystemdeeplearningandmachinelearningapproachesforultrasoundimageanalysis |