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http://dx.doi.org/10.5909/JBE.2013.18.3.401

Classification based Knee Bone Detection using Context Information  

Shin, Seungyeon (Automation and Systems Research Institute, Department of Electrical and Computer Engineering, Seoul National University)
Park, Sanghyun (Automation and Systems Research Institute, Department of Electrical and Computer Engineering, Seoul National University)
Yun, Il Dong (School of Digital Information Engineering, Hankuk University of Foreign Studies)
Lee, Sang Uk (Automation and Systems Research Institute, Department of Electrical and Computer Engineering, Seoul National University)
Publication Information
Journal of Broadcast Engineering / v.18, no.3, 2013 , pp. 401-408 More about this Journal
Abstract
In this paper, we propose a method that automatically detects organs having similar appearances in medical images by learning both context and appearance features. Since only the appearance feature is used to learn the classifier in most existing detection methods, detection errors occur when the medical images include multiple organs having similar appearances. In the proposed method, based on the probabilities acquired by the appearance-based classifier, new classifier containing the context feature is created by iteratively learning the characteristics of probability distribution around the interest voxel. Furthermore, both the efficiency and the accuracy are improved through 'region based voting scheme' in test stage. To evaluate the performance of the proposed method, we detect femur and tibia which have similar appearance from SKI10 knee joint dataset. The proposed method outperformed the detection method only using appearance feature in aspect of overall detection performance.
Keywords
Classification; Knee Bone; Detection; Context;
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