Automatic Pediatric Otitis Detection by Classification of Global Image Features

被引：0
|
作者：
Mironica, Ionut [1 ]
Vertan, Constantin [1 ]
Gheorghe, Dan Cristian [2 ]
机构：
[1] Univ Politehn Bucuresti, Image Proc & Anal Lab, Bucharest, Romania
[2] Univ Med Pharm, Marie Curie Clin Pediat Otorhinolaringology, Bucharest, Romania
来源：
2011 E-HEALTH AND BIOENGINEERING CONFERENCE (EHB) | 2011年
关键词：
Otitis Diagnosis; k-Nearest Neighbor; Decision Trees; Linear Discriminant Analysis; Naive Bayes; Multi Layer Neural Networks; Support Vector Machines; TELE-OTOLOGY;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
This paper proposes a preliminary study regarding the implementation of a pediatric otorhinolaryngology diagnosis support system for the visual diagnosis of the eardrum, based on the automatic evaluation by digital image processing techniques of the otoscopic digital color images of the eardrum. We compare different color descriptors and classification algorithms (k-Nearest Neighbor, Decision Trees, Linear Discriminant Analysis, Naive Bayes, Multi Layer Neural Networks and Support Vector Machines) and try to choose the best solution in terms of performance/computation to be included in an integrated framework.
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收藏
页数：4
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