Non-sparse infinite-kernel learning for automated identification of Alzheimer's disease using PET imaging

Yong Xia, Shen Lu, Wei Wei, David Dagan Feng, Yanning Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

Multi-kernel learning machine (MKLM) has recently been introduced to the research of computer-aided dementia identification and pathology progress tracking. Despite its good performance especially in case of using heterogeneous data, such learning schema and its variants usually utilize a L-l norm constraint that promotes sparse solutions, which may cause loss of potentially important information. In this paper, we propose the non-sparse infinite-kernel learning machine (NS-IKLM) for automated identification of Alzheimer cases from normal controls. In our approach, a modified constraint is utilized to promotes non-sparse solutions and kernel parameters are automatically tuned during the learning process. The proposed algorithm has been evaluated on a set of FDG-PET images selected from the Alzheimer's disease neuroimaing initiative (ADNI) cohort. Our results demonstrate that the proposed non-sparse NS-IKLM is able to achieve satisfying dementia identification at a relatively low computational cost.

源语言英语
主期刊名2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
出版商Institute of Electrical and Electronics Engineers Inc.
855-860
页数6
ISBN(电子版)9781479951994
DOI
出版状态已出版 - 2014
活动2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014 - Singapore, 新加坡
期限: 10 12月 201412 12月 2014

出版系列

姓名2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014

会议

会议2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014
国家/地区新加坡
Singapore
时期10/12/1412/12/14

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