CAB-Net: Channel Attention Block Network for Pathological Image Cell Nucleus Segmentation
文献类型：会议论文
| 作者 | Li, Meixuan3; Fan HJ(范慧杰)1,2 ; Yang, Dawei3
|
| 出版日期 | 2021 |
| 会议日期 | August 6-8, 2021 |
| 会议地点 | Haikou, China |
| 关键词 | Nucleus segmentation Attention models Deep learning |
| 页码 | 654-663 |
| 英文摘要 | In histopathological image analysis, cell nucleus segmentation plays an important role in the clinical analysis and diagnosis of cancer. However, due to the different morphology of cells, uneven staining and the existence of a large number of dense nuclei, it is still challenging to accurately segment the nucleus. In order to learn more specific key feature information during the training process, this paper proposed a network model called the CAB-Net that uses channel attention to enhance the learning of feature information on each channel. The network uses the channel attention mechanism to extract the key features in each channel, generates weights to judge the importance of the features, and then weights them into the original image. This aims to strengthen the extraction of key information, thereby generating a more characteristic feature map, and enabling the model to make more accurate judgments. We added a boundary smoothness constraint, in order to better identify cell nuclei with unclear boundaries and achieve more accurate cell nucleus segmentation. The experimental results show that the method in this paper achieves good performance on the cell segmentation data set. |
| 产权排序 | 2 |
| 会议录 | Image and Graphics - 11th International Conference, ICIG 2021, Proceedings
 |
| 会议录出版者 | Springer Science and Business Media Deutschland GmbH |
| 会议录出版地 | Berlin |
| 语种 | 英语 |
| ISSN号 | 0302-9743 |
| ISBN号 | 978-3-030-87357-8 |
| 源URL | [http://ir.sia.cn/handle/173321/29781]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Fan HJ(范慧杰) |
| 作者单位 | 1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 3.School of Information Technology and Engineering, Shenyang Ligong University, Liaoning, Shenyang 110159, China |
| 推荐引用方式 GB/T 7714 | Li, Meixuan,Fan HJ,Yang, Dawei. CAB-Net: Channel Attention Block Network for Pathological Image Cell Nucleus Segmentation[C]. 见:. Haikou, China. August 6-8, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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