图 书 馆
医学图像的层次注释Hierarchical Annotation of Medical Images |
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| 课程网址: | http://videolectures.net/sikdd08_dimitrovski_hami/ |
| 主讲教师: | Ivica Dimitrovski |
| 开课单位: | 约瑟夫·斯特凡学院 |
| 开课时间: | 2008-11-07 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper, we describe an approach for the automatic medical annotation task of the 2008 CLEF cross-language image retrieval campaign (ImageCLEF). The data comprise 12076 fully annotated images according to the IRMA code. This work is focused on the process of feature extraction from images and hierarchical multi-label classification. To extract features from the images we used a technique called: local distribution of edges. With this techniques each image was described with 80 variables. The goal of the classification task was to classify an image according to the IRMA code. The IRMA code is organized hierarchically. Hence, as classifer we selected an extension of the predictive clustering trees (PCTs) that is able to handle this type of data. Further more, we constructed ensembles (Bagging and Random Forests) that use PCTs as base classifiers. |
| 关 键 词: | 图像分析; 计算机视觉; CLEF跨语言图像检索运动 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-07-28：yumf |
| 阅读次数: | 108 |