Metastatic Breast Cancer Recognition in Histopathology Images Using Convolutional Neural Network with Attention Mechanism
- Resource Type
- Conference
- Authors
- Liang, Yu; Yang, Jinglong; Quan, Xiongwen; Zhang, Han
- Source
- 2019 Chinese Automation Congress (CAC) Chinese Automation Congress (CAC), 2019. :2922-2926 Nov, 2019
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Breast cancer
Pathology
Training
Task analysis
Convolutional neural networks
neural network
breast cancer
histopathology
attention mechanism
- Language
- ISSN
- 2688-0938
Lymph node tissue pathological analysis is one of the common methods for doctors to evaluate the types and stage of breast cancer. Using deep learning methods to detect breast cancer metastases has great research value. We proposes a model to automatically classify breast cancer metastases, using a convolutional neural network with attention mechanism. A Convolutional Block Attention Module is used in our network. We validate our model on PCam dataset, and obtain an AUC score of 0.976. These results demonstrate that using computer vision method has a great performance in pathological diagnoses.