{"title":"面向健康图像库构建的疾病表现图像检索方法","authors":"Yang Chen, Xiaofeng Ren, Guo-Qiang Zhang, Rong Xu","doi":"10.1109/HISB.2012.32","DOIUrl":null,"url":null,"abstract":"Building a comprehensive medical image database, in the spirit of the UMLS, can be beneficial for assisting diagnosis, patient education and self-care. However, a highly curated, comprehensive image database is difficult to collect as well as to annotate. We present an approach to combine visual object detection technologies with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling. Comparing to a supervised approach, our ontology-guided approach reduces manual labeling effort to 1/10 on a variety of eye/ear/mouth diseases and improves the precision of retrieval by over 10% in many cases.","PeriodicalId":375089,"journal":{"name":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ontology-Guided Approach to Retrieving Disease Manifestation Images for Health Image Base Construction\",\"authors\":\"Yang Chen, Xiaofeng Ren, Guo-Qiang Zhang, Rong Xu\",\"doi\":\"10.1109/HISB.2012.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Building a comprehensive medical image database, in the spirit of the UMLS, can be beneficial for assisting diagnosis, patient education and self-care. However, a highly curated, comprehensive image database is difficult to collect as well as to annotate. We present an approach to combine visual object detection technologies with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling. Comparing to a supervised approach, our ontology-guided approach reduces manual labeling effort to 1/10 on a variety of eye/ear/mouth diseases and improves the precision of retrieval by over 10% in many cases.\",\"PeriodicalId\":375089,\"journal\":{\"name\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HISB.2012.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HISB.2012.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontology-Guided Approach to Retrieving Disease Manifestation Images for Health Image Base Construction
Building a comprehensive medical image database, in the spirit of the UMLS, can be beneficial for assisting diagnosis, patient education and self-care. However, a highly curated, comprehensive image database is difficult to collect as well as to annotate. We present an approach to combine visual object detection technologies with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling. Comparing to a supervised approach, our ontology-guided approach reduces manual labeling effort to 1/10 on a variety of eye/ear/mouth diseases and improves the precision of retrieval by over 10% in many cases.
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