Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

Deep learning, as one of the currently most popular computer science research trends,
improves neural networks, which has more and deeper layers allowing higher abstraction …

Breast cancer is the second most common cancer in women who are mainly middle-aged
and older. The American Cancer Society reported that the average risk of develo** breast …

Breast histopathology analysis is the gold standard for diagnosing breast cancer.
Convolutional neural network-based methods for breast histology image classification have …

Pathology image classification plays an important role in cancer diagnosis and precision
treatment. Convolutional neural network has been widely employed in pathology image …

Attention mechanism is crucial in the auxiliary diagnosis of breast cancer. However,
methods relying on a single attention mechanism may not always achieve satisfactory …

Deep learning has substantially improved the state-of-the-art in object detection and image
classification. Deep learning usually requires large-scale labelled datasets to train the …

Background Deep learning tasks, which require large numbers of images, are widely
applied in digital pathology. This poses challenges especially for supervised tasks since …

Background: Breast cancer is one of the most lethal cancers among women. Early detection
and proper treatment reduce mortality rates. Histopathological images provide detailed …

Computer aided diagnosis has become upcoming area of research over past few years.
With the advent of machine learning and especially deep learning techniques, the scenario …