In this paper, we have proposed a method for breast cancer classification with the Inception Recurrent Residual Convolutional Neural Network (IRRCNN) model. The IRRCNN is a powerful DCNN model that combines the strength of the Inception Network (Inception-v4), the Residual Network (ResNet), and...
Automated breast cancer multi-classification from histopathological images plays a key role in computer-aided breast cancer diagnosis or prognosis. Breast cancer multi-classification is to identify subordinate classes of breast cancer (Ductal carcinoma, Fibroadenoma, Lobular carcinoma, etc.). However, breas...
Deep learning has been used extensively in histopathological image classification, but people in this field are still exploring new neural network architectures for more effective and efficient cancer diagnosis. Here, we propose multi-scale, multi-view p
Breast cancer is one of the most serious types of cancer that can occur in women. The automatic diagnosis of breast cancer by analyzing histological images (HIs) is important for patients and their prognosis. The classification of HIs provides clinicians with an accurate understanding of diseases a...
Classification of breast cancer histology images using transfer learning 一、数据集: BACH 2018 grand challenge (ICIAR 2018 Grand Challenge on BreAst Cancer Histology images) https://iciar2018-challenge.grand-challenge.org/home/ 其实算得上Camelyon 16和17 的后继版本。
This paper proposes a classification method based on Complex Event Processing (CEP) for mammogram images. For breast cancer detection and early prevention, several factors must be considered. Mammogram is important and effective in breast cancer diagnosis. The Radiologist must analyze visually, based on...
Breast cancer (BC) continues to be a prominent issue in global public health, emphasizing the need for precise and timely detection. This paper employs a deep learning (DL) approach to introduce an extensive methodology for categorizing histopathology images associated with breast cancer into automated...
Breast cancer is a common malignancy and a leading cause of cancer-related deaths in women worldwide. Its early diagnosis can significantly reduce the morbidity and mortality rates in women. To this end, histopathological diagnosis is usually followed as
Nowadays, the classification of medical images has become an essential part of identifying the disease. Among various existing critical diseases, identification of breast cancer has now come up with the topic of investigation. To identify the affected regions of the images, a deep learning-based app...
Breast Cancer Classification from Histopathological Images using Future Search Optimization Algorithm and Deep Learning In medical imaging, precise recognition of Breast Cancer (BC) is a challenge due to the complications of breast tissues. Histopathological detection is sti... R Gurumoorthy,M Kamarasan...