基于多目标遗传规划的肝活检图像纤维化检测

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI:10.1109/ICITEED.2017.8250486

Purit Thong-on, U. Watchareeruetai

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引用次数: 2

摘要

本文提出了一种基于多目标遗传规划方法的肝纤维化检测特征提取器的自动构建方法，其中构建的特征提取器在不同方面进行测量，从而成为进化运行的目标。进化运行的结果是一组具有不同优点和缺点的解决方案。从每个实验中选择一个解决方案，并通过每个实验和前五种方法与基准手工方法进行比较。得到的最佳结果之一的纤维化估计误差为2.09，小于基准方法的纤维化估计误差2.63。

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Detection of fibrosis in liver biopsy images using multi-objective genetic programming

This paper proposes an automatic construction of feature extractor for liver fibrosis detection using a multiobjective genetic programming approach in which a constructed feature extractor was measured in different aspects in which becomes the objectives of the evolutionary run. The result of the evolutionary run is a set of solutions with different strengths and weaknesses. A solution from each experiment is selected and compared with a benchmark handcraft method in by each experiment and top-five manners. One of the best result obtained has 2.09 fibrosis estimation error which is less than the benchmark method with 2.63 fibrosis estimation error.

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2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)

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