{"title":"基于体素分析的支持向量机肺结节计算机辅助检测","authors":"Yang Liu, Jinzhu Yang, Dazhe Zhao, Jiren Liu","doi":"10.1109/FBIE.2009.5405784","DOIUrl":null,"url":null,"abstract":"The detection of pulmonary nodules is proven to be of critical importance in early-stage lung cancer diagnosis. Many computer aided detection (CAD) methods combined with morphological approach and pattern recognition technology to identify lung nodules have been proposed to assist the radiologists to improve sensitivity of diagnosis. We present a computer aided lung nodule detection scheme based on analysis of enhanced voxel in three dimensional (3D) CT image. The method is multi-step, including lung fields segmentation, initial nodule candidates enhancement, enhanced voxel feature extraction, voxels classification with support vector machines (SVMs) and nodule decision rule. Two lung nodule data sets are employed to evaluate the performance of the computerized scheme. The experimental results illustrate the efficiency of the proposed method. We intend to improve the voxel enhancement procedure to increase the performance of the scheme.","PeriodicalId":333255,"journal":{"name":"2009 International Conference on Future BioMedical Information Engineering (FBIE)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Computer aided detection of lung nodules based on voxel analysis utilizing support vector machines\",\"authors\":\"Yang Liu, Jinzhu Yang, Dazhe Zhao, Jiren Liu\",\"doi\":\"10.1109/FBIE.2009.5405784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The detection of pulmonary nodules is proven to be of critical importance in early-stage lung cancer diagnosis. Many computer aided detection (CAD) methods combined with morphological approach and pattern recognition technology to identify lung nodules have been proposed to assist the radiologists to improve sensitivity of diagnosis. We present a computer aided lung nodule detection scheme based on analysis of enhanced voxel in three dimensional (3D) CT image. The method is multi-step, including lung fields segmentation, initial nodule candidates enhancement, enhanced voxel feature extraction, voxels classification with support vector machines (SVMs) and nodule decision rule. Two lung nodule data sets are employed to evaluate the performance of the computerized scheme. The experimental results illustrate the efficiency of the proposed method. We intend to improve the voxel enhancement procedure to increase the performance of the scheme.\",\"PeriodicalId\":333255,\"journal\":{\"name\":\"2009 International Conference on Future BioMedical Information Engineering (FBIE)\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Future BioMedical Information Engineering (FBIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FBIE.2009.5405784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Future BioMedical Information Engineering (FBIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FBIE.2009.5405784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computer aided detection of lung nodules based on voxel analysis utilizing support vector machines
The detection of pulmonary nodules is proven to be of critical importance in early-stage lung cancer diagnosis. Many computer aided detection (CAD) methods combined with morphological approach and pattern recognition technology to identify lung nodules have been proposed to assist the radiologists to improve sensitivity of diagnosis. We present a computer aided lung nodule detection scheme based on analysis of enhanced voxel in three dimensional (3D) CT image. The method is multi-step, including lung fields segmentation, initial nodule candidates enhancement, enhanced voxel feature extraction, voxels classification with support vector machines (SVMs) and nodule decision rule. Two lung nodule data sets are employed to evaluate the performance of the computerized scheme. The experimental results illustrate the efficiency of the proposed method. We intend to improve the voxel enhancement procedure to increase the performance of the scheme.