The early diagnosis of breast cancer using pathological images is of the vital importance.
Recently, breast cancer histopathology image classification methods based on convolution …

Computer‐aided classification of pathological images is of the great significance for breast
cancer diagnosis. In recent years, deep learning methods for breast cancer pathological …

Histopathological image analysis is an important technique for early diagnosis and detection
of breast cancer in clinical practice. However, it has limited efficiency and thus the detection …

With the breakthrough performance in a variety of computer vision and medical image
analysis problems, convolutional neural networks (CNNs) have been successfully …

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

In this study, we proposed a novel convolutional neural network (CNN) architecture for
classification of benign and malignant breast cancer (BC) in histological images. To improve …

Researches on breast cancer histopathological image classification have achieved a great
breakthrough using deep backbones of Convolutional Neural Networks (CNNs) in recent …

Breast cancer is the cancer with the highest incidence of malignant tumors in women, which
seriously endangers women's health. With the help of computer vision technology, it has …

Breast cancer (BC) is the third leading cause of deaths in women globally. In general,
histopathology images are recommended for early diagnosis and detailed analysis for BC …

Background Breast cancer has the highest prevalence among all cancers in women
globally. The classification of histopathological images in the diagnosis of breast cancers is …