A Multiscale-Based Adjustable Convolutional Neural Network for Multiple Organ Segmentation
文献类型：期刊论文
| 作者 | Tian, Zhiqiang2; Song, Jingyi2; Zhang, Chenyang2; Tian, Xiaohui2; Shi, Zhong1,3; Yu, Xiaofu1,3 |
| 刊名 | WIRELESS COMMUNICATIONS & MOBILE COMPUTING
 |
| 出版日期 | 2020-08-03 |
| 卷号 | 2020 |
| ISSN号 | 1530-8669 |
| DOI | 10.1155/2020/9595687 |
| 通讯作者 | Tian, Zhiqiang(zhiqiangtian@xjtu.edu.cn) |
| 英文摘要 | Accurate segmentation ofs organs-at-risk (OARs) in computed tomography (CT) is the key to planning treatment in radiation therapy (RT). Manually delineating OARs over hundreds of images of a typical CT scan can be time-consuming and error-prone. Deep convolutional neural networks with specific structures like U-Net have been proven effective for medical image segmentation. In this work, we propose an end-to-end deep neural network for multiorgan segmentation with higher accuracy and lower complexity. Compared with several state-of-the-art methods, the proposed accuracy-complexity adjustment module (ACAM) can increase segmentation accuracy and reduce the model complexity and memory usage simultaneously. An attention-based multiscale aggregation module (MAM) is also proposed for further improvement. Experiment results on chest CT datasets show that the proposed network achieves competitive Dice similarity coefficient results with fewer float-point operations (FLOPs) for multiple organs, which outperforms several state-of-the-art methods. |
| 资助项目 | NSFC[61876148] ; Fundamental Research Funds for the Central Universities[XJJ2018254] ; China Postdoctoral Science Foundation[2018M631164] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000562871300004 |
| 出版者 | WILEY-HINDAWI |
| 资助机构 | NSFC ; Fundamental Research Funds for the Central Universities ; China Postdoctoral Science Foundation |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/43126]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Tian, Zhiqiang |
| 作者单位 | 1.Univ Chinese Acad Sci, Canc Hosp, Hangzhou 310022, Peoples R China 2.Xi An Jiao Tong Univ, Sch Software Engn, Xian 710049, Peoples R China 3.Chinese Acad Sci, Inst Canc & Basic Med ICBM, Hangzhou 310022, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tian, Zhiqiang,Song, Jingyi,Zhang, Chenyang,et al. A Multiscale-Based Adjustable Convolutional Neural Network for Multiple Organ Segmentation[J]. WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2020,2020. |
| APA | Tian, Zhiqiang,Song, Jingyi,Zhang, Chenyang,Tian, Xiaohui,Shi, Zhong,&Yu, Xiaofu.(2020).A Multiscale-Based Adjustable Convolutional Neural Network for Multiple Organ Segmentation.WIRELESS COMMUNICATIONS & MOBILE COMPUTING,2020. |
| MLA | Tian, Zhiqiang,et al."A Multiscale-Based Adjustable Convolutional Neural Network for Multiple Organ Segmentation".WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2020(2020). |
入库方式： OAI收割
来源：合肥物质科学研究院
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