A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
[HTML][HTML] Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review
The relatively recent reintroduction of deep learning has been a revolutionary force in the
interpretation of diagnostic imaging studies. However, the technology used to acquire those …
interpretation of diagnostic imaging studies. However, the technology used to acquire those …
Survey on machine learning and deep learning applications in breast cancer diagnosis
Cancer is a fatal disease caused due to the undesirable spread of cells. Breast carcinoma is
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …
the most invasive tumors and is the main reason for cancer deaths in females. Therefore …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
A comprehensive investigation of multimodal deep learning fusion strategies for breast cancer classification
In breast cancer research, diverse data types and formats, such as radiological images,
clinical records, histological data, and expression analysis, are employed. Given the intricate …
clinical records, histological data, and expression analysis, are employed. Given the intricate …
Shape-based breast lesion classification using digital tomosynthesis images: The role of explainable artificial intelligence
Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
including classification and staging of the various diseases. The 3D tomosynthesis imaging …
Deep learning in selected cancers' image analysis—a survey
TG Debelee, SR Kebede, F Schwenker… - Journal of …, 2020 - mdpi.com
Deep learning algorithms have become the first choice as an approach to medical image
analysis, face recognition, and emotion recognition. In this survey, several deep-learning …
analysis, face recognition, and emotion recognition. In this survey, several deep-learning …
Deep learning in breast radiology: current progress and future directions
This review provides an overview of current applications of deep learning methods within
breast radiology. The diagnostic capabilities of deep learning in breast radiology continue to …
breast radiology. The diagnostic capabilities of deep learning in breast radiology continue to …
A competition, benchmark, code, and data for using artificial intelligence to detect lesions in digital breast tomosynthesis
Importance An accurate and robust artificial intelligence (AI) algorithm for detecting cancer in
digital breast tomosynthesis (DBT) could significantly improve detection accuracy and …
digital breast tomosynthesis (DBT) could significantly improve detection accuracy and …
[HTML][HTML] Breast cancer detection and analytics using hybrid cnn and extreme learning machine
V Sureshkumar, RSN Prasad… - Journal of Personalized …, 2024 - mdpi.com
Early detection of breast cancer is essential for increasing survival rates, as it is one of the
primary causes of death for women globally. Mammograms are extensively used by …
primary causes of death for women globally. Mammograms are extensively used by …