A fusion method based on Deep Learning and Case-Based Reasoning which improves the resulting medical image segmentations

作者：

Highlights：

• This paper proposes a DL-CBR method for the fusion of segmentations.

• This method has been applied to 9 children with an average of 109 slices per patient.

• Tumours and kidneys were segmented separately and merged through our method.

• Results obtained resolved all the conflicts and improved the overall segmentations.

摘要

•This paper proposes a DL-CBR method for the fusion of segmentations.•This method has been applied to 9 children with an average of 109 slices per patient.•Tumours and kidneys were segmented separately and merged through our method.•Results obtained resolved all the conflicts and improved the overall segmentations.

论文关键词：Fusion,Conflict management,Segmentation,Cancer tumour,Deep learning,Case-based reasoning

论文评审过程：Received 9 September 2019, Revised 23 December 2019, Accepted 10 January 2020, Available online 11 January 2020, Version of Record 18 January 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113200