Classification of breast cancer histology images using Convolutional Neural Networks
Universidade do Porto · Institute for Systems Engineering and Computers · +2 more institutions
Abstract
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 disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs) is proposed.…
Citation impact
- FWCI
- 77.83
- Percentile
- 100%
- References
- 30
Authors
8- TATeresa AraújoCorresponding
Universidade do Porto, Institute for Systems Engineering and Computers, INESC TEC
- GAGuilherme Aresta
Universidade do Porto, Institute for Systems Engineering and Computers, INESC TEC
- ECEduardo Castro
Universidade do Porto
- JRJosé Rouco
Institute for Systems Engineering and Computers, INESC TEC
- PAPaulo Aguiar
Universidade do Porto, i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto
Topics & keywords
- Artificial intelligence
- Convolutional neural network
- H&E stain
- Breast cancer
- Computer science
- Pattern recognition (psychology)
- Breast carcinoma
- Classifier (UML)
- Good health and well-being