A spatially constrained skew Student’s-t mixture model for brain MR image segmentation and bias field correction

作者：

Highlights：

• We proposed anisotropic spatial information to reduce the effect of noise and preserve more details.

• We use Skew Student’s-t mixture model to fit the intensity distributions of the images with asymmetric forms.

• Our method can obtain more accurate results.

摘要

•We proposed anisotropic spatial information to reduce the effect of noise and preserve more details.•We use Skew Student’s-t mixture model to fit the intensity distributions of the images with asymmetric forms.•Our method can obtain more accurate results.

论文关键词：Bias field,EM Algorithm,Skew student’s-t distribution,Two-level spatial information

论文评审过程：Received 23 October 2021, Revised 2 March 2022, Accepted 14 March 2022, Available online 16 March 2022, Version of Record 23 March 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2022.108658