Segmentation of deformed kidneys and nephroblastoma using Case-Based Reasoning and Convolutional Neural Network

作者：

Highlights：

• This paper suggests two methods based on AI tools for medical image segmentation.

• The first method uses CBR to guide a region-growing process for segmentation.

• The second method based on Deep Learning performs segmentation with a small data set.

• Both methods were tested on CT-scans images from children with tumoral kidneys .

• They provided accurate enough results to consider an automatic. segmentation

摘要

•This paper suggests two methods based on AI tools for medical image segmentation.•The first method uses CBR to guide a region-growing process for segmentation.•The second method based on Deep Learning performs segmentation with a small data set.•Both methods were tested on CT-scans images from children with tumoral kidneys .•They provided accurate enough results to consider an automatic. segmentation

论文关键词：Case-based reasoning,Convolutional neural networks,Image segmentation,Tumor,Healthcare imaging,Deep learning

论文评审过程：Received 20 September 2018, Revised 5 March 2019, Accepted 5 March 2019, Available online 9 March 2019, Version of Record 18 March 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.03.010