Breast cancer detection using deep learning: Datasets, methods, and challenges ahead
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC …
[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
Classification of breast cancer histology images using convolutional neural networks
Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy
tissue with hematoxylin and eosin stained images is non-trivial and specialists often …
tissue with hematoxylin and eosin stained images is non-trivial and specialists often …
Breast cancer detection using deep convolutional neural networks and support vector machines
It is important to detect breast cancer as early as possible. In this manuscript, a new
methodology for classifying breast cancer using deep learning and some segmentation …
methodology for classifying breast cancer using deep learning and some segmentation …
A framework for breast cancer classification using multi-DCNNs
Background Deep learning (DL) is the fastest-growing field of machine learning (ML). Deep
convolutional neural networks (DCNN) are currently the main tool used for image analysis …
convolutional neural networks (DCNN) are currently the main tool used for image analysis …
Breast cancer detection using extreme learning machine based on feature fusion with CNN deep features
A computer-aided diagnosis (CAD) system based on mammograms enables early breast
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …
A novel hybrid deep learning model for metastatic cancer detection
Cancer has been found as a heterogeneous disease with various subtypes and aims to
destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis …
destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis …
Breast cancer classification using machine learning
M Amrane, S Oukid, I Gagaoua… - 2018 electric electronics …, 2018 - ieeexplore.ieee.org
During their life, among 8% of women are diagnosed with Breast cancer (BC), after lung
cancer, BC is the second popular cause of death in both developed and undeveloped …
cancer, BC is the second popular cause of death in both developed and undeveloped …
Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review
NIR Yassin, S Omran, EMF El Houby… - Computer methods and …, 2018 - Elsevier
Background and objective The high incidence of breast cancer in women has increased
significantly in the recent years. Physician experience of diagnosing and detecting breast …
significantly in the recent years. Physician experience of diagnosing and detecting breast …