Name
Title | ||
|---|---|---|
A dense connection encoding–decoding convolutional neural network structure for semantic segmentation of thymoma |
Abstract | ||
|---|---|---|
•Three-channel pseudo-color images preprocessing method is designed by concatenating different CT windows.•A dense skip connection encoding–decoding model (DSC-Net) is proposed to perform automatic segmentation of thymoma base on a deep convolutional neural network.•Dense connections are introduced into the architecture of the encoding path across different level feature maps in the DSC-Net.•Different level skip connections are designed between the encoding and decoding path in the DSC-Net. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.neucom.2021.04.023 | Neurocomputing |
Keywords | DocType | Volume |
Thymoma,Computed tomography,Convolutional neural network,Image processing | Journal | 451 |
ISSN | Citations | PageRank |
0925-2312 | 1 | 0.41 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingyuan Li | 1 | 20 | 8.86 |
| Wenfang Sun | 2 | 1 | 0.75 |
| Xiulong Feng | 3 | 1 | 0.41 |
| Gang Xing | 4 | 1 | 0.41 |
| Karen M. von Deneen | 5 | 1 | 0.75 |
| Wen Wang | 6 | 2 | 2.16 |
| Yi Zhang | 7 | 1 | 1.09 |
| Guangbin Cui | 8 | 3 | 2.85 |