Computer aided endoscope diagnosis via weakly labeled data mining
文献类型：会议论文
| 作者 | Wang S(王帅) ; Cong Y(丛杨); Fan HJ(范慧杰); Yang YS(杨云生); Tang YD(唐延东); Zhao HC(赵怀慈)
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| 出版日期 | 2015 |
| 会议名称 | 2015 IEEE International Conference on Image Processing (ICIP) |
| 会议日期 | September 27-30, 2015 |
| 会议地点 | Quebec City, QC, Canada |
| 关键词 | Computer aided diagnosis (CAD) multiple instance learning (MIL) weakly labeled endoscope images |
| 页码 | 3072-3076 |
| 中文摘要 | In comparison to most computer aided endoscope diagnosis methods using pixel-wise groundtruth by physicians manually, it is easy to get lots of endoscope images with corresponding diagnostic reports. In this paper, we intend to mine pixel-wise label information from these reports with weak frame-level labels automatically. To achieve this, we formulate our computer aided diagnosis problem as a Multiple Instance Learning (MIL) issue, where we represent each image as superpixels. Each image and each superpixel is cast as bag and instance, respectively. We then evaluate and select the most positive instances from positive bags automatically which helps us transform the frame-level classification problem into a standard supervised learning problem. In the experiment, we build a new gastroscopic image dataset with more than 3000 weakly labeled images, and ours outperforms the state-of-the-art methods, which verifies the effectiveness of our model. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2015 IEEE International Conference on Image Processing (ICIP)
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| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 英语 |
| ISBN号 | 978-1-4799-8339-1 |
| WOS记录号 | WOS:000371977803040 |
| 源URL | [http://ir.sia.cn/handle/173321/17466]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | Wang S,Cong Y,Fan HJ,et al. Computer aided endoscope diagnosis via weakly labeled data mining[C]. 见:2015 IEEE International Conference on Image Processing (ICIP). Quebec City, QC, Canada. September 27-30, 2015. |
入库方式： OAI收割
来源：沈阳自动化研究所
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