Name
Title | ||
|---|---|---|
A Discriminative Level Set Method with Deep Supervision for Breast Tumor Segmentation |
Abstract | ||
|---|---|---|
•A novel, deeply supervised network is devised for breast tumor segmentation.•A discriminative level-set method is integrated at different stages of the network.•A new feature-discriminator is added to the level set method’s energy function.•Feature-discriminator improves model ability to identify hazy regions preciously.•The ensembling in the level set group suppresses the false-positive.•The proposed model can locate the more reliable malignant regions.•Experiments on multiple datasets affirm the success and effectiveness of the model. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.compbiomed.2022.105995 | Computers in Biology and Medicine |
Keywords | DocType | Volume |
Deep learning,Medical image segmentation,Discriminative information,Level set | Journal | 149 |
ISSN | Citations | PageRank |
0010-4825 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sumaira Hussain | 1 | 4 | 2.10 |
| Xiaoming Xi | 2 | 250 | 24.80 |
| Inam Ullah | 3 | 0 | 0.34 |
| Syed Azeem Inam | 4 | 0 | 0.34 |
| Farah Naz | 5 | 0 | 0.34 |
| Kashif Shaheed | 6 | 0 | 0.34 |
| Syed Asif Ali | 7 | 0 | 0.34 |
| Cuihuan Tian | 8 | 0 | 0.34 |