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Computer aided endoscope diagnosis via weakly labeled data mining
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)
作者部门机器人学研究室
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
会议录名称2015 IEEE International Conference on Image Processing (ICIP)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码3072-3076
收录类别EI ; CPCI(ISTP)
EI收录号20160601896363
WOS记录号WOS:000371977803040
产权排序1
ISBN号978-1-4799-8339-1
关键词Computer Aided Diagnosis (Cad) Multiple Instance Learning (Mil) Weakly Labeled Endoscope Images
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.
语种英语
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被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17466
专题机器人学研究室
通讯作者Wang S(王帅)
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, China
2.University of Chinese Academy of Sciences, China
3.Chinese PLA General Hospital, China
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]. Piscataway, NJ, USA:IEEE,2015:3072-3076.
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