Gaussian process classification of superparamagnetic relaxometry data: Phantom study
作者：
Highlights：
• Classification of superparamagnetic relaxometry data was considered.
• We used a Gaussian process model and an image reconstruction technique.
• Our in silico and phantom studies verified the superiority of Gaussian process model.
摘要
•Classification of superparamagnetic relaxometry data was considered.•We used a Gaussian process model and an image reconstruction technique.•Our in silico and phantom studies verified the superiority of Gaussian process model.
论文关键词：Superparamagnetic relaxometry,Weak source detection,Gaussian process
论文评审过程：Received 6 March 2017, Revised 14 June 2017, Accepted 3 July 2017, Available online 24 July 2017, Version of Record 26 October 2017.
论文官网地址：https://doi.org/10.1016/j.artmed.2017.07.001
