Name
Title | ||
|---|---|---|
Deep Neural Networks with Region-based Pooling Structures for Mammographic Image Classification. |
Abstract | ||
|---|---|---|
Breast cancer is one of the most frequently diagnosed solid cancers. Mammography is the most commonly used screening technology for detecting breast cancer. Traditional machine learning methods of mammographic image classification or segmentation using manual features require a great quantity of manual segmentation annotation data to train the model and test the results. But manual labeling is exp... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TMI.2020.2968397 | IEEE Transactions on Medical Imaging |
Keywords | DocType | Volume |
Feature extraction,Lesions,Breast cancer,Annotations,Image segmentation | Journal | 39 |
Issue | ISSN | Citations |
6 | 0278-0062 | 5 |
PageRank | References | Authors |
0.41 | 0 | 5 |