| 题名 | Multi-Task Classification and Segmentation for Explicable Capsule Endoscopy Diagnostics |
| 作者 | |
| 发表日期 | 2021-08-19 |
| 发表期刊 | Frontiers in Molecular Biosciences
 |
| 卷号 | 8 |
| 摘要 | Capsule endoscopy is a leading diagnostic tool for small bowel lesions which faces certain challenges such as time-consuming interpretation and harsh optical environment inside the small intestine. Specialists unavoidably waste lots of time on searching for a high clearness degree image for accurate diagnostics. However, current clearness degree classification methods are based on either traditional attributes or an unexplainable deep neural network. In this paper, we propose a multi-task framework, called the multi-task classification and segmentation network (MTCSN), to achieve joint learning of clearness degree (CD) and tissue semantic segmentation (TSS) for the first time. In the MTCSN, the CD helps to generate better refined TSS, while TSS provides an explicable semantic map to better classify the CD. In addition, we present a new benchmark, named the Capsule-Endoscopy Crohn’s Disease dataset, which introduces the challenges faced in the real world including motion blur, excreta occlusion, reflection, and various complex alimentary scenes that are widely acknowledged in endoscopy examination. Extensive experiments and ablation studies report the significant performance gains of the MTCSN over state-of-the-art methods. |
| 关键词 | Auxiliary diagnosis Capsule endoscopy Crohn’s disease Explicable Multi-task learning |
| DOI | 10.3389/fmolb.2021.614277 |
| URL | 查看来源 |
| 语种 | 英语English |
| Scopus入藏号 | 2-s2.0-85114348924 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/5973 |
| 专题 | 北师香港浸会大学 |
| 通讯作者 | Chen，Jie |
| 作者单位 | 1.School of Electonic and Computer Engineering,Peking University,Shenzhen,China 2.Department of Gastroenterology,Peking University Shenzhen Hospital,Shenzhen,China 3.Peng Cheng Laboratory,Shenzhen,China 4.Sun Yat-sen University,Guangzhou,China 5.Pennsylvania State University,Philadelphia,United States 6.Harbin Institute of Technology (Shenzhen),Shenzhen,China 7.Beijing Normal University-Hong Kong Baptist University United International College,Zhuhai,China |
| 推荐引用方式 GB/T 7714 | Kong，Zishang,He，Min,Luo，Qianjianget al. Multi-Task Classification and Segmentation for Explicable Capsule Endoscopy Diagnostics[J]. Frontiers in Molecular Biosciences, 2021, 8. |
| APA | Kong，Zishang., He，Min., Luo，Qianjiang., Huang，Xiansong., Wei，Pengxu., .. & Chen，Jie. (2021). Multi-Task Classification and Segmentation for Explicable Capsule Endoscopy Diagnostics. Frontiers in Molecular Biosciences, 8. |
| MLA | Kong，Zishang,et al."Multi-Task Classification and Segmentation for Explicable Capsule Endoscopy Diagnostics". Frontiers in Molecular Biosciences 8(2021). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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