Parasite worm egg automatic detection in microscopy stool image based on Faster R-CNN

被引:17
作者
Ngo Quoc Viet [1 ]
Dang Thi ThanhTuyen [1 ]
Trinh Huy Hoang [1 ]
机构
[1] HCMC Univ Educ, 280 An Dung Vuong,D5, Hcmc, Vietnam
来源
PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND SOFT COMPUTING (ICMLSC 2019) | 2019年
关键词
Parasite worm eggs; object detection; CNN; Fast R-CNN; Faster R-CNN;
D O I
10.1145/3310986.3311014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposed a method based on Faster R-CNN for detection of human parasite eggs in stool images. The shapes, and patterns of parasite worm in egg micro images are very diversity, therefore proposing and choosing the good model to detect them is necessary to help the doctors discover the potential disease by worm in human. To be sure for the proposal, we executed many various experiments, and retrieved dataset from two independent resources. The training set is retrieved in standard biology image library, meanwhile the evaluation image set is retrieved from real patients. The precision, recall and other values evaluated in the experiments represented the effectiveness of the method. The various experiments with the outstanding results proved the correctness of the proposal.
引用
收藏
页码:197 / 202
页数:6
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