{"title":"数字放射影像中肺结节的特征提取与检测算法","authors":"Cesar Supanta, G. Kemper, C. D. Carpio","doi":"10.1109/ICA-ACCA.2018.8609795","DOIUrl":null,"url":null,"abstract":"This work proposes a method for feature extraction and detection of pulmonary nodules in digital radiographic images, as little visualization and highlighting of these features often prevent a deeper diagnosis in chest radiographs. The proposed method involves digital image processing techniques such as re-quantization, gamma correction, OTSU thresholding, projection analysis, convergence filter, dilation, erosion and geometric filters. The proposed algorithm has a sensitivity of 91%, specificity of 96% and precision 94% with a referential database of 50 chest radiographs.","PeriodicalId":176587,"journal":{"name":"2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"An algorithm for feature extraction and detection of pulmonary nodules in digital radiographic images\",\"authors\":\"Cesar Supanta, G. Kemper, C. D. Carpio\",\"doi\":\"10.1109/ICA-ACCA.2018.8609795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work proposes a method for feature extraction and detection of pulmonary nodules in digital radiographic images, as little visualization and highlighting of these features often prevent a deeper diagnosis in chest radiographs. The proposed method involves digital image processing techniques such as re-quantization, gamma correction, OTSU thresholding, projection analysis, convergence filter, dilation, erosion and geometric filters. The proposed algorithm has a sensitivity of 91%, specificity of 96% and precision 94% with a referential database of 50 chest radiographs.\",\"PeriodicalId\":176587,\"journal\":{\"name\":\"2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICA-ACCA.2018.8609795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICA-ACCA.2018.8609795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An algorithm for feature extraction and detection of pulmonary nodules in digital radiographic images
This work proposes a method for feature extraction and detection of pulmonary nodules in digital radiographic images, as little visualization and highlighting of these features often prevent a deeper diagnosis in chest radiographs. The proposed method involves digital image processing techniques such as re-quantization, gamma correction, OTSU thresholding, projection analysis, convergence filter, dilation, erosion and geometric filters. The proposed algorithm has a sensitivity of 91%, specificity of 96% and precision 94% with a referential database of 50 chest radiographs.