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