Subject-Specific prior shape knowledge in feature-oriented probability maps for fully automatized liver segmentation in MR volume data

作者：

Highlights：

• Fully automatized liver segmentation approach for native MR volume data

• Subject-specific prior liver shape incorporation into level set segmentation

• Liver tissue-specific probability map generation combining all MR contrasts

• Consideration of inner-organ MR-differences and recognition of fat livers and cysts

• Novel alignment and attraction techniques for exact liver delineation

摘要

•Fully automatized liver segmentation approach for native MR volume data•Subject-specific prior liver shape incorporation into level set segmentation•Liver tissue-specific probability map generation combining all MR contrasts•Consideration of inner-organ MR-differences and recognition of fat livers and cysts•Novel alignment and attraction techniques for exact liver delineation

论文关键词：Expectation maximization,Subject-specific shape model,3D prior shape level set segmentation,Bayesian probability,Normalized cross correlation,Principal component analysis

论文评审过程：Received 12 June 2016, Revised 17 May 2018, Accepted 16 July 2018, Available online 19 July 2018, Version of Record 28 July 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.07.018