R. Hayashibe, N. Asano, H. Hirohata, K. Okumura, S. Kondo, S. Handa, M. Takizawa, S. Sone, S. Oshita
{"title":"通过每年的连续质量调查获得的x射线图像自动检测肺癌","authors":"R. Hayashibe, N. Asano, H. Hirohata, K. Okumura, S. Kondo, S. Handa, M. Takizawa, S. Sone, S. Oshita","doi":"10.1109/ICIP.1996.559503","DOIUrl":null,"url":null,"abstract":"A fully automatic method of detecting new lung nodules based on the subtraction method between two serial mass chest radiographs is proposed. Nodule detection is carried out following the three steps: pre-processing, subtraction and post-processing. In the pre-processing step, the outline of the bilateral lungs is extracted and modified in order to perform good subtraction between the two images to be compared. In the post-processing step, limitation and localization of candidate nodules of lung cancer are carried out. In these two steps, an evaluator function called \"simpleness\" of a single connection region is applied to identify outline of the lung and to select candidates of cancer(s).","PeriodicalId":192947,"journal":{"name":"Proceedings of 3rd IEEE International Conference on Image Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"An automatic lung cancer detection from X-ray images obtained through yearly serial mass survey\",\"authors\":\"R. Hayashibe, N. Asano, H. Hirohata, K. Okumura, S. Kondo, S. Handa, M. Takizawa, S. Sone, S. Oshita\",\"doi\":\"10.1109/ICIP.1996.559503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A fully automatic method of detecting new lung nodules based on the subtraction method between two serial mass chest radiographs is proposed. Nodule detection is carried out following the three steps: pre-processing, subtraction and post-processing. In the pre-processing step, the outline of the bilateral lungs is extracted and modified in order to perform good subtraction between the two images to be compared. In the post-processing step, limitation and localization of candidate nodules of lung cancer are carried out. In these two steps, an evaluator function called \\\"simpleness\\\" of a single connection region is applied to identify outline of the lung and to select candidates of cancer(s).\",\"PeriodicalId\":192947,\"journal\":{\"name\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd IEEE International Conference on Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.1996.559503\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd IEEE International Conference on Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1996.559503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An automatic lung cancer detection from X-ray images obtained through yearly serial mass survey
A fully automatic method of detecting new lung nodules based on the subtraction method between two serial mass chest radiographs is proposed. Nodule detection is carried out following the three steps: pre-processing, subtraction and post-processing. In the pre-processing step, the outline of the bilateral lungs is extracted and modified in order to perform good subtraction between the two images to be compared. In the post-processing step, limitation and localization of candidate nodules of lung cancer are carried out. In these two steps, an evaluator function called "simpleness" of a single connection region is applied to identify outline of the lung and to select candidates of cancer(s).