Accelerating Neuroimage Registration through Parallel Computation of Similarity Metric
Publication in refereed journal


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摘要Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT with the correlation ratio (CR) as the similarity metric and a GPU accelerated correlation coefficient (CC) calculation for the symmetric diffeomorphic registration of ANTs have been developed. The comparison with their corresponding original tools shows that our accelerated algorithms can greatly outperform the original algorithm in terms of computational efficiency. This paper demonstrates the great potential of applying these registration tools in clinical applications.
著者Luo YG, Liu P, Shi L, Luo YS, Yi L, Li A, Qin J, Heng PA, Wang DF
期刊名稱PLoS ONE
出版年份2015
月份9
日期9
卷號10
期次9
出版社PUBLIC LIBRARY SCIENCE
國際標準期刊號1932-6203
語言英式英語
Web of Science 學科類別Multidisciplinary Sciences; Science & Technology - Other Topics

上次更新時間 2020-24-10 於 02:43