Emerging role of deep learning‐based artificial intelligence in tumor pathology
The development of digital pathology and progression of state‐of‐the‐art algorithms for
computer vision have led to increasing interest in the use of artificial intelligence (AI) …
computer vision have led to increasing interest in the use of artificial intelligence (AI) …
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of …
Artificial intelligence for breast cancer analysis: Trends & directions
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …
cancer can significantly improve the lives of millions of women across the globe. Given …
Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images
Breast cancer tumor grade is strongly associated with patient survival. In current clinical
practice, pathologists assign tumor grade after visual analysis of tissue specimens …
practice, pathologists assign tumor grade after visual analysis of tissue specimens …
A comprehensive survey on deep-learning-based breast cancer diagnosis
Simple Summary Breast cancer was diagnosed in 2.3 million women, and around 685,000
deaths from breast cancer were recorded globally in 2020, making it the most common …
deaths from breast cancer were recorded globally in 2020, making it the most common …
Breast histopathological image analysis using image processing techniques for diagnostic purposes: A methodological review
Breast cancer in women is the second most common cancer worldwide. Early detection of
breast cancer can reduce the risk of human life. Non-invasive techniques such as …
breast cancer can reduce the risk of human life. Non-invasive techniques such as …
Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological …
Abstract Computer-aided Invasive Ductal Carcinoma (IDC) grading classification systems
based on deep learning have shown that deep learning may achieve reliable accuracy in …
based on deep learning have shown that deep learning may achieve reliable accuracy in …
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 review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks
Breast cancer is currently the second most common cause of cancer-related death in
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
women. Presently, the clinical benchmark in cancer diagnosis is tissue biopsy examination …
Mitotic nuclei analysis in breast cancer histopathology images using deep ensemble classifier
Mitotic nuclei estimation in breast tumour samples has a prognostic significance in analysing
tumour aggressiveness and grading system. The automated assessment of mitotic nuclei is …
tumour aggressiveness and grading system. The automated assessment of mitotic nuclei is …