CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm

作者：

Highlights：

• Hybrid approach based on NS, Watershed, and fast FCM algorithms for automatic CT liver tumor segmentation.

• Results demonstrate that, neutrosophy can handle indeterminacy, uncertainty, and reduce over-segmentation.

• The over-all accuracy obtained from the proposed approach almost 95% of good liver segmentation.

• This results can help for further diagnosis and treatment planning.

摘要

•Hybrid approach based on NS, Watershed, and fast FCM algorithms for automatic CT liver tumor segmentation.•Results demonstrate that, neutrosophy can handle indeterminacy, uncertainty, and reduce over-segmentation.•The over-all accuracy obtained from the proposed approach almost 95% of good liver segmentation.•This results can help for further diagnosis and treatment planning.

论文关键词：

论文评审过程：Received 14 March 2018, Revised 9 September 2018, Accepted 25 November 2018, Available online 14 December 2018, Version of Record 13 June 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2018.11.007