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Detection of fibrosis in liver biopsy images using multi-objective genetic programming
Author(s)
Thong-On, Purit
Watchareeruetai, Ukrit
Date Issued
July 1, 2017
Type
Conference Paper
Abstract
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.
Citation
2017 9th International Conference on Information Technology and Electrical Engineering Icitee 2017, 2018-January, 1-6, 2017